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https://api.github.com/repos/huggingface/transformers/issues/4212 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4212/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4212/comments | https://api.github.com/repos/huggingface/transformers/issues/4212/events | https://github.com/huggingface/transformers/issues/4212 | 614,220,806 | MDU6SXNzdWU2MTQyMjA4MDY= | 4,212 | GPT2Tokenizer.decode() slow for individual tokens | {
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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"
] | 1,588 | 1,594 | 1,594 | NONE | null | `GPT2Tokenizer.decode()` is considerable slow when invoking it for each token individually, not for a set of tokens... I need to pass in a set of tokens and get back a set of strings for each token. I tried convert_ids_to_tokens() but I'm getting results with the Ġ character. Should I simply remove that character from ... | {
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https://api.github.com/repos/huggingface/transformers/issues/4211 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4211/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4211/comments | https://api.github.com/repos/huggingface/transformers/issues/4211/events | https://github.com/huggingface/transformers/pull/4211 | 614,204,002 | MDExOlB1bGxSZXF1ZXN0NDE0ODA2MjQ2 | 4,211 | W&B integration improvements | {
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"^^ I borked your PR unfortunately (💩). Sorry about that. Care to open a new one?"
] | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | Hey guys,
I'm one of the founders of W&B and have been working with @borisdayma on the wandb integration. I made a few changes to address a few cases we thought through:
1. If wandb is installed but the user hasn't logged in we now print a warning instead of prompting for an api_key
2. Made messaging more clear... | {
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https://api.github.com/repos/huggingface/transformers/issues/4210 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4210/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4210/comments | https://api.github.com/repos/huggingface/transformers/issues/4210/events | https://github.com/huggingface/transformers/issues/4210 | 614,202,590 | MDU6SXNzdWU2MTQyMDI1OTA= | 4,210 | Perplexity in T5/BART | {
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"T5 uses CrossEntropy loss so I think you can use `torch.exp(loss)` to calculate perplexity.",
"Thanks!",
"@patil-suraj Sorry to bother you again, I thought my problem has been solved, but I don't know how to deal with the loss. It's a (1,1,vocab_size) tensor. I don't even have an intuition about what that mean... | 1,588 | 1,609 | 1,588 | NONE | null | Hi,
Is there a way to compute perplexity for T5 or BART outputs? | {
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https://api.github.com/repos/huggingface/transformers/issues/4209 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4209/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4209/comments | https://api.github.com/repos/huggingface/transformers/issues/4209/events | https://github.com/huggingface/transformers/pull/4209 | 614,178,429 | MDExOlB1bGxSZXF1ZXN0NDE0Nzg1MDMz | 4,209 | Fix for IndexError when Roberta Tokenizer is called on empty text | {
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Fix for https://github.com/huggingface/transformers/issues/3809 | {
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https://api.github.com/repos/huggingface/transformers/issues/4208 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4208/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4208/comments | https://api.github.com/repos/huggingface/transformers/issues/4208/events | https://github.com/huggingface/transformers/pull/4208 | 614,157,176 | MDExOlB1bGxSZXF1ZXN0NDE0NzY3ODE2 | 4,208 | Remove comma that turns int into tuple | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4208?src=pr&el=h1) Report\n> Merging [#4208](https://codecov.io/gh/huggingface/transformers/pull/4208?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/cafa6a9e29f3e99c67a1028f8ca779d439bc0689&el=desc) will **decrease... | 1,588 | 1,588 | 1,588 | MEMBER | null | cf @stefan-it's error on Slack | {
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https://api.github.com/repos/huggingface/transformers/issues/4207 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4207/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4207/comments | https://api.github.com/repos/huggingface/transformers/issues/4207/events | https://github.com/huggingface/transformers/issues/4207 | 614,151,196 | MDU6SXNzdWU2MTQxNTExOTY= | 4,207 | BertForTokenClassification, logits on sequence tagging task | {
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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"
] | 1,588 | 1,594 | 1,594 | NONE | null | # ❓ Questions & Help
## Details
<!-- Description of your issue -->
I'm trying to use BertForTokenClassification to do a sequence tagging task. During training, everything seems fine and loss is decreasing per epoch, but when I put the model in evaluation mode and feed it inputs, the logits for each token are all t... | {
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https://api.github.com/repos/huggingface/transformers/issues/4206 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4206/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4206/comments | https://api.github.com/repos/huggingface/transformers/issues/4206/events | https://github.com/huggingface/transformers/issues/4206 | 614,136,128 | MDU6SXNzdWU2MTQxMzYxMjg= | 4,206 | How to get output from BERTNextSentencePrediction by passing One Sentence and Next Sentence getting predicted | {
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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"
] | 1,588 | 1,594 | 1,594 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/4205 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4205/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4205/comments | https://api.github.com/repos/huggingface/transformers/issues/4205/events | https://github.com/huggingface/transformers/issues/4205 | 614,132,175 | MDU6SXNzdWU2MTQxMzIxNzU= | 4,205 | Issues with RobertaTokenizer and unicode characters | {
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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"
] | 1,588 | 1,595 | 1,595 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
Roberta
Language I am using the model on (English, Chinese ...):
English
## To reproduce
Steps to reproduce the behavior:
1. Insert a jumble of some weird unicode characters into the vocabulary file. These unicode characters must exist on t... | {
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https://api.github.com/repos/huggingface/transformers/issues/4204 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4204/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4204/comments | https://api.github.com/repos/huggingface/transformers/issues/4204/events | https://github.com/huggingface/transformers/issues/4204 | 614,117,788 | MDU6SXNzdWU2MTQxMTc3ODg= | 4,204 | KeyError with a fine-tuned model | {
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"How many labels/entities are there in your model ? Can you check if the key 422 exists in the models config's id2label by printing it or by opening the config file. You can print config using `model.config` ",
"Hello\r\nIt seems I had simply been misusing my model : I was instantiating an `AutoModel`, when I sho... | 1,588 | 1,588 | 1,588 | NONE | null | I've fine-tuned the allenai's scibert to do some NER using the `run_ner.py` script, but I keep bumping into a key error. My code is the following:
```
m = AutoModel.from_pretrained("models/sciBERT_ner_e50/")
tok = AutoTokenizer.from_pretrained("allenai/scibert_scivocab_uncased")
nlp = pipeline("ner", model=m, token... | {
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https://api.github.com/repos/huggingface/transformers/issues/4203 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4203/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4203/comments | https://api.github.com/repos/huggingface/transformers/issues/4203/events | https://github.com/huggingface/transformers/pull/4203 | 614,109,244 | MDExOlB1bGxSZXF1ZXN0NDE0NzI4ODM5 | 4,203 | Use with_suffix to change the extension of the path | {
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https://api.github.com/repos/huggingface/transformers/issues/4201 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4201/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4201/comments | https://api.github.com/repos/huggingface/transformers/issues/4201/events | https://github.com/huggingface/transformers/pull/4201 | 614,082,670 | MDExOlB1bGxSZXF1ZXN0NDE0NzA3MDM4 | 4,201 | Ensure fast tokenizer can construct single-element tensor without pad token | {
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https://api.github.com/repos/huggingface/transformers/issues/4200 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4200/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4200/comments | https://api.github.com/repos/huggingface/transformers/issues/4200/events | https://github.com/huggingface/transformers/issues/4200 | 614,079,056 | MDU6SXNzdWU2MTQwNzkwNTY= | 4,200 | [Proposal] Small HfAPI Cleanup | {
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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"
] | 1,588 | 1,594 | 1,594 | CONTRIBUTOR | null | - Implement __dict__ and __str__ so that one need not guess the class attributes of `ModelInfo` and `S3Object`
- Delete redundant `S3Obj` class. (`S3Object` seems to be a superset).
- Rename to `HFApi`?
Thoughts @julien-c @LysandreJik ? | {
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https://api.github.com/repos/huggingface/transformers/issues/4199 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4199/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4199/comments | https://api.github.com/repos/huggingface/transformers/issues/4199/events | https://github.com/huggingface/transformers/pull/4199 | 614,058,964 | MDExOlB1bGxSZXF1ZXN0NDE0Njg3NTQ0 | 4,199 | [README] Corrected some grammatical mistakes | {
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"Thanks for your contribution @girishponkiya , merging!"
] | 1,588 | 1,589 | 1,589 | CONTRIBUTOR | null | Corrected some grammatical mistakes, like added required punctuation marks, corrected singular-plural mistakes, etc. | {
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https://api.github.com/repos/huggingface/transformers/issues/4198 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4198/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4198/comments | https://api.github.com/repos/huggingface/transformers/issues/4198/events | https://github.com/huggingface/transformers/pull/4198 | 614,050,271 | MDExOlB1bGxSZXF1ZXN0NDE0NjgwMzQ1 | 4,198 | [Benchmark] Memory benchmark utils | {
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"This google colab shows nicely how the new benchmarking utils can be used: https://colab.research.google.com/drive/1GM3WPXmZ5wZHwhdPyf7RykJS3Y12iceJ?usp=sharing",
"A plotter file is included in `examples/benchmarking` which can give the following results:\r\n\r\n### Memory\r\n\r\n![memory_example](https://user-i... | 1,588 | 1,590 | 1,590 | MEMBER | null | ## Description
Currently, we have a benchmarks file in examples `examples/benchmarks.py` which measures time and speed for inference and one `src/transformers/benchmark_utils.py` file which including the memory tracing from @thomwolf.
This PR generalizes the benchmarks much more:
- We have `benchmark_args_utils,... | {
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https://api.github.com/repos/huggingface/transformers/issues/4197 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4197/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4197/comments | https://api.github.com/repos/huggingface/transformers/issues/4197/events | https://github.com/huggingface/transformers/issues/4197 | 614,044,933 | MDU6SXNzdWU2MTQwNDQ5MzM= | 4,197 | AutoTokenizer not able to load saved Roberta Tokenizer | {
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"It looks like when you load a tokenizer from a dir it's also looking for files to load it's related model config via `AutoConfig.from_pretrained`. It does this because it's using the information from the config to to determine which model class the tokenizer belongs to (BERT, XLNet, etc ...) since there is no way ... | 1,588 | 1,595 | 1,595 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): Roberta
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [x] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
I'm trying to run `run_languag... | {
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https://api.github.com/repos/huggingface/transformers/issues/4195 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4195/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4195/comments | https://api.github.com/repos/huggingface/transformers/issues/4195/events | https://github.com/huggingface/transformers/pull/4195 | 613,986,159 | MDExOlB1bGxSZXF1ZXN0NDE0NjI4NzUx | 4,195 | add XLMRobertaForQuestionAnswering | {
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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",
"Closing since already implemented"
] | 1,588 | 1,596 | 1,596 | CONTRIBUTOR | null | 1. add XLMRobertaForQuestionAnswering in modeling_xlm_roberta.py
2. add XLMRobertaForQuestionAnswering in modeling_auto.py | {
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https://api.github.com/repos/huggingface/transformers/issues/4194 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4194/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4194/comments | https://api.github.com/repos/huggingface/transformers/issues/4194/events | https://github.com/huggingface/transformers/pull/4194 | 613,970,377 | MDExOlB1bGxSZXF1ZXN0NDE0NjE2MDY1 | 4,194 | Optimize PyTorch's GPT2 computation graph | {
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"GPT2 Attention has `merge_heads` method which takes an input as `(batch, heads, seq, repr)` and outputs the flattened _(merged)_ representation of it `(batch, seq, heads * repr)`. \r\n\r\n```python\r\n def merge_heads(self, x):\r\n x = x.transpose(2, 1).contiguous()\r\n new_x_shape = x.size()[:-2]... | 1,588 | 1,651 | 1,595 | MEMBER | null | Brings various optimizations to make the computation graph more efficient. | {
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"This is currently not supported. There used to be some community maintained examples IIRC. You can have a look here: https://github.com/huggingface/transformers/tree/1.1.0/examples/lm_finetuning\r\n\r\n"
] | 1,588 | 1,588 | 1,588 | NONE | null | When using "run_language_modeling.py" for fine-tuning BERT is only the MLM task used or also the NSP task as described in the paper? | {
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https://api.github.com/repos/huggingface/transformers/issues/4192 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4192/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4192/comments | https://api.github.com/repos/huggingface/transformers/issues/4192/events | https://github.com/huggingface/transformers/pull/4192 | 613,887,461 | MDExOlB1bGxSZXF1ZXN0NDE0NTUwMTE0 | 4,192 | [Reformer] Doctsring: fix examples again | {
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https://api.github.com/repos/huggingface/transformers/issues/4191 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4191/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4191/comments | https://api.github.com/repos/huggingface/transformers/issues/4191/events | https://github.com/huggingface/transformers/pull/4191 | 613,877,002 | MDExOlB1bGxSZXF1ZXN0NDE0NTQxNzMy | 4,191 | [Reformer] Fix example and error message | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4191?src=pr&el=h1) Report\n> Merging [#4191](https://codecov.io/gh/huggingface/transformers/pull/4191?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/96c78396ce1baf5e19c0618689005f93c7f42d79&el=desc) will **decrease... | 1,588 | 1,588 | 1,588 | MEMBER | null | Fix typos and improve error message. | {
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https://api.github.com/repos/huggingface/transformers/issues/4190 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4190/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4190/comments | https://api.github.com/repos/huggingface/transformers/issues/4190/events | https://github.com/huggingface/transformers/pull/4190 | 613,871,447 | MDExOlB1bGxSZXF1ZXN0NDE0NTM3MzM4 | 4,190 | [Reformer] fix docstring | {
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https://api.github.com/repos/huggingface/transformers/issues/4189 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4189/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4189/comments | https://api.github.com/repos/huggingface/transformers/issues/4189/events | https://github.com/huggingface/transformers/issues/4189 | 613,762,901 | MDU6SXNzdWU2MTM3NjI5MDE= | 4,189 | Bug: can not use pretrained BERT on multiple GPUs with DataParallel (PyTorch 1.5.0) | {
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"By the way, when I downgrade Pytorch 1.5.0 to 1.4.0, the error disappears. ",
"The same issue: #3936",
"Closing in favor of #3936"
] | 1,588 | 1,589 | 1,589 | NONE | null | Python: 3.6.10
PyTorch: 1.5.0
Transformers: 2.8.0 and 2.9.0
In the following code, I wrap the pretrained BERT with a DataParallel wrapper so as to run it on multiple GPUs:
> import torch, transformers
> model = transformers.AutoModel.from_pretrained("bert-base-multilingual-cased")
> model = torch.nn.DataParal... | {
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https://api.github.com/repos/huggingface/transformers/issues/4188 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4188/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4188/comments | https://api.github.com/repos/huggingface/transformers/issues/4188/events | https://github.com/huggingface/transformers/pull/4188 | 613,722,647 | MDExOlB1bGxSZXF1ZXN0NDE0NDIxMDgx | 4,188 | Fix Albert Attention | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4188?src=pr&el=h1) Report\n> Merging [#4188](https://codecov.io/gh/huggingface/transformers/pull/4188?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/877fc56410e3a0495f62e07e66a73e6b3b9629bc&el=desc) will **increase... | 1,588 | 1,594 | 1,594 | CONTRIBUTOR | null | This PR simplifies the code of class AlbertAttention. | {
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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"
] | 1,588 | 1,594 | 1,594 | NONE | null | Hello,
Reading the tutorial [Language Translation with torchText](https://pytorch.org/tutorials/beginner/torchtext_translation_tutorial.html) I wondered how someone could use those convenience classes (`Field, BucketIterator`) to train/fine-tune a `Transformer`.
For instance, I'm currently working with a large data... | {
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https://api.github.com/repos/huggingface/transformers/issues/4186 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4186/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4186/comments | https://api.github.com/repos/huggingface/transformers/issues/4186/events | https://github.com/huggingface/transformers/pull/4186 | 613,634,282 | MDExOlB1bGxSZXF1ZXN0NDE0MzUxNjEy | 4,186 | Add patience argument to Trainer | {
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"This supercedes https://github.com/huggingface/transformers/pull/2840, where I added patience to the outdated `run_language_modeling.py` script.",
"Looking good! Can you add a reference to your original post that this closes https://github.com/huggingface/transformers/issues/4894? Thanks",
"Hello, when this fe... | 1,588 | 1,606 | 1,606 | NONE | null | This closes #4894.
# Summary
Often, we want to stop training if loss does not improve for a number of epochs. This PR adds a "patience" argument, which is a limit on the number of times we can get a non-improving eval loss before stopping training early.
It is implemented by other NLP frameworks, such as AllenNL... | {
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https://api.github.com/repos/huggingface/transformers/issues/4185 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4185/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4185/comments | https://api.github.com/repos/huggingface/transformers/issues/4185/events | https://github.com/huggingface/transformers/issues/4185 | 613,618,890 | MDU6SXNzdWU2MTM2MTg4OTA= | 4,185 | New model request: MobileBERT from Google | {
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"https://github.com/lonePatient/MobileBert_PyTorch",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"This was completed in #4901"
] | 1,588 | 1,595 | 1,595 | CONTRIBUTOR | null | # 🌟 New model addition
This issue is to request adding the MobileBERT model, which was recently released by Carnegie Mellon University, Google Research, and Google Brain.
## Model description
MobileBERT is a more computationally-efficient model for achieving BERT-base level accuracy on a smartphone.
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https://api.github.com/repos/huggingface/transformers/issues/4184 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4184/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4184/comments | https://api.github.com/repos/huggingface/transformers/issues/4184/events | https://github.com/huggingface/transformers/pull/4184 | 613,575,969 | MDExOlB1bGxSZXF1ZXN0NDE0MzAzNzcy | 4,184 | Model card for allegro/herbert-klej-cased-tokenizer-v1 | {
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https://api.github.com/repos/huggingface/transformers/issues/4183 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4183/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4183/comments | https://api.github.com/repos/huggingface/transformers/issues/4183/events | https://github.com/huggingface/transformers/pull/4183 | 613,574,017 | MDExOlB1bGxSZXF1ZXN0NDE0MzAyMTkw | 4,183 | Model card for allegro/herbert-klej-cased-v1 | {
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"Great work and great model cards, congrats on beating the state-of-the-art of Polish NLU!",
"Thanks!"
] | 1,588 | 1,589 | 1,588 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4182 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4182/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4182/comments | https://api.github.com/repos/huggingface/transformers/issues/4182/events | https://github.com/huggingface/transformers/issues/4182 | 613,560,540 | MDU6SXNzdWU2MTM1NjA1NDA= | 4,182 | Is it possible to get document embeddings using GPT-2? If so, how? | {
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"Not from Huggingface, but for this, I would use something like SentenceBERT. As far as I know.",
"@moinnadeem Thank you for pointing me in that direction! But would sentencebert really work for documents?",
"This issue has been automatically marked as stale because it has not had recent activity. It will be cl... | 1,588 | 1,594 | 1,594 | NONE | null | # ❓ Questions & Help
I posted a question here on SO: https://stackoverflow.com/questions/61641257/how-to-get-document-embeddings-using-gpt-2?noredirect=1#comment109035633_61641257
But unfortunately was informed that "Please notice that SO is not a tutorial service, and also that recommendation requests for extern... | {
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https://api.github.com/repos/huggingface/transformers/issues/4181 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4181/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4181/comments | https://api.github.com/repos/huggingface/transformers/issues/4181/events | https://github.com/huggingface/transformers/issues/4181 | 613,503,438 | MDU6SXNzdWU2MTM1MDM0Mzg= | 4,181 | [Marian] Key-Error for some languages | {
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"marian C++ code uses `<unk>` in this case"
] | 1,588 | 1,589 | 1,589 | CONTRIBUTOR | null | model -> symbol that caused `KeyError`.
```python
{'ha-en': '|',
'ber-es': '▁Be',
'pis-fi': '▁|',
'es-mt': '|',
'fr-he': '₫',
'niu-sv': 'OGI',
'fi-fse': '▁rentou',
'fi-mh': '|',
'hr-es': '|',
'fr-ber': '▁devr',
'ase-en': 'olos'}
```
Reproduce
```python
pair = 'ber-es'
mname = f'Helsinki... | {
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https://api.github.com/repos/huggingface/transformers/issues/4180 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4180/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4180/comments | https://api.github.com/repos/huggingface/transformers/issues/4180/events | https://github.com/huggingface/transformers/pull/4180 | 613,477,467 | MDExOlB1bGxSZXF1ZXN0NDE0MjIzNzY3 | 4,180 | considering empty input text to avoid string index out of range error | {
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] | 1,588 | 1,594 | 1,594 | NONE | null | When the input string is empty, the above condition in the tokenization_roberta will encounter string index out of range error. For example, a pair input string exists in the QQP dataset that has an empty string:
{'idx': 362246,
'label': 0,
'question1': b'How can I develop android app?',
'question2': b''} | {
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https://api.github.com/repos/huggingface/transformers/issues/4179 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4179/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4179/comments | https://api.github.com/repos/huggingface/transformers/issues/4179/events | https://github.com/huggingface/transformers/pull/4179 | 613,417,949 | MDExOlB1bGxSZXF1ZXN0NDE0MTc1ODI1 | 4,179 | Create README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4179?src=pr&el=h1) Report\n> Merging [#4179](https://codecov.io/gh/huggingface/transformers/pull/4179?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ff8ed52dd8c6268f2535c0721cde9e360fbb0ce0&el=desc) will **not chan... | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | model card for my De Novo Drug discovery model using MLM | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4178?src=pr&el=h1) Report\n> Merging [#4178](https://codecov.io/gh/huggingface/transformers/pull/4178?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ff8ed52dd8c6268f2535c0721cde9e360fbb0ce0&el=desc) will **decrease... | 1,588 | 1,589 | 1,589 | CONTRIBUTOR | null | - Generated using tools in `convert_marian_to_pytorch.py`.
- Takes the bottom most entry in each opus-mt-train/models/*/README.md. This assumes that the bottom entry is most recent. (Created by @jorgtied).
- Example below is at `model_cards/Helsinki-NLP/opus-mt-fr-en/README.md`
__________________________
# opus-2... | {
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https://api.github.com/repos/huggingface/transformers/issues/4177 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4177/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4177/comments | https://api.github.com/repos/huggingface/transformers/issues/4177/events | https://github.com/huggingface/transformers/issues/4177 | 613,337,980 | MDU6SXNzdWU2MTMzMzc5ODA= | 4,177 | Not able to import certain packages | {
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"You need to make sure you install from source as documented in the README"
] | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | # 🐛 Bug
## Information
- I am using `run_glue.py`.
- Working with GLUE
## To reproduce
Steps to reproduce the behavior:
Even though these functions are imported in `__init__.py` (I have thoroughly checked myself), I'm not able to import `EvalPrediction`, `HfArgumentParser`, `Trainer`, `TrainingArguments`... | {
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https://api.github.com/repos/huggingface/transformers/issues/4176 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4176/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4176/comments | https://api.github.com/repos/huggingface/transformers/issues/4176/events | https://github.com/huggingface/transformers/pull/4176 | 613,251,933 | MDExOlB1bGxSZXF1ZXN0NDE0MDQxMDMz | 4,176 | ONNX conversion script. | {
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Plan is to support both PyTorch and TensorFlow:
- [x] PyTorch
- [ ] TensorFlow
TensorFlow currently blocked because of an issue in the conversion script provided by ONNX (seems fixed on master : https://github.com/onnx/tensorflow-onnx/issues/87... | {
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https://api.github.com/repos/huggingface/transformers/issues/4175 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4175/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4175/comments | https://api.github.com/repos/huggingface/transformers/issues/4175/events | https://github.com/huggingface/transformers/issues/4175 | 613,181,942 | MDU6SXNzdWU2MTMxODE5NDI= | 4,175 | args.output_dir seems like been ignored | {
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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"
] | 1,588 | 1,594 | 1,594 | NONE | null | https://github.com/huggingface/transformers/blob/a638e986f45b338c86482e1c13e045c06cfeccad/examples/run_squad.py#L814
It seems that args.output_dir is been ignored in checkpoints when args.eval_all_checkpoints is True.
It probably should be like this:
global_step = checkpoint.split("-")[-1] if (len(checkpoints) > 1 ... | {
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"Thanks for contributing #4173 :)."
] | 1,588 | 1,589 | 1,589 | CONTRIBUTOR | null | # 🚀 Feature request
Make `ElectraPreTrainedModel` importable
## Motivation
Consistency.
`DistilBertPreTrainedModel` and `AlbertPreTrainedModel` are importable but I cannot import `ElectraPretrainedModel` from v2.8.0
(see https://github.com/huggingface/transformers/issues/1968)
## Your contribution
h... | {
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https://api.github.com/repos/huggingface/transformers/issues/4172 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4172/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4172/comments | https://api.github.com/repos/huggingface/transformers/issues/4172/events | https://github.com/huggingface/transformers/issues/4172 | 613,097,429 | MDU6SXNzdWU2MTMwOTc0Mjk= | 4,172 | ImportError: cannot import name 'AutoModel' from 'transformers' | {
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"Got the same result with 2.9.0, i.e. with `# pip install tensorflow==2.0 transformers==2.9.0`",
"`AutoModel` is the equivalent of `TFAutoModel` but for PyTorch model classes. If you don't have pytorch installed this is expected.\r\n\r\nUse `TFAutoModel` instead =)\r\n\r\n",
"Thank you!",
"@julien-c \r\nBut t... | 1,588 | 1,661 | 1,588 | NONE | null | # 🐛 Bug
(Not sure that it is a bug, but it is too easy to reproduce I think)
## Information
I couldn't run `python -c 'from transformers import AutoModel'`, instead getting the error on the titile.
## To reproduce
Steps to reproduce the behavior:
1. `$ sudo docker run -it --rm python:3.6 bash`
2. `#... | {
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"Are you using this exact line\r\n```\r\nmodel = EncoderDecoderModel.from_encoder_decoder_pretrained('bert-base-uncased', 'bert-base-uncased') # initialize Bert2Bert\r\n```\r\nIf yes, then please use paths for your saved model. Few other things to try: verify data pipeline,\r\ntry using beam search or sampling in g... | 1,588 | 1,595 | 1,588 | NONE | null | Hello! I tried to train a Bert2Bert model for QA generation, however when I try the generate function it returns gibberish. I also tried using the example code below, and that also generated gibberish(the output is "[PAD] leon leon leon leon leonieieieieie shall shall shall shall shall shall shall shall shall"). Is the... | {
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"You don't need to provide position IDs to the model, the model will create them on its own. Similarly to the `attention_mask` and `token_type_ids`, you only need to provide them if you want them to be different to the default.\r\n\r\nIn the case of position IDs, provide them if you want to use a special scheme/dif... | 1,588 | 1,595 | 1,595 | NONE | null | BertTokenizer provide us with input_ids, attention_mask and token_type_ids but i'm unable to get so called "Position ids".
I have read the documentation as well but unable to find anything. | {
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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",
"The issue was resolved."
] | 1,588 | 1,594 | 1,594 | NONE | null | https://github.com/huggingface/transformers/issues/4168 | {
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"Hi, you can import it as such:\r\n```py\r\nfrom transformers.modeling_albert import AlbertMLMHead\r\n```\r\n\r\nIt's not in the `__init.py__` as it's not a model but part of one."
] | 1,588 | 1,589 | 1,589 | NONE | null | # 🌟 New model addition
## Model description
MLM model head
```
No name 'AlbertMLMHead' in module 'transformers'
```
## Open source status
* [x] the model implementation is available:
```
class AlbertMLMHead(nn.Module):
def __init__(self, config):
super().__init__()
self.Layer... | {
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"hey, @thomwolf this would be a great addition! have a look into it.",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.\n",
"I think @NielsRogge is working on this over here: https://gith... | 1,588 | 1,602 | 1,595 | CONTRIBUTOR | null | # 🌟 New model addition
## Model descriptin
Tapas extends Bert architecture and is a transformer-based Table QA model
Paper: https://arxiv.org/abs/2004.02349
## Open source status
* [X] the model implementation is available: (give details)
https://github.com/google-research/tapas
* [X] the model weight... | {
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"(note that this will need to be refined to work with TF / beam search if we decide on the direction)",
"Closing in favor of #5416 "
] | 1,588 | 1,593 | 1,593 | NONE | null | See https://github.com/huggingface/transformers/issues/4164 | {
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"Very interesting idea! I think we eventually have to make the generation function more general anyways. \r\n\r\nMaybe it's time to move this whole code:\r\n\r\n```python \r\n # repetition penalty from CTRL paper (https://arxiv.org/abs/1909.05858)\r\n if repetition_penalty != 1.0:\r\n ... | 1,588 | 1,599 | 1,599 | NONE | null | # 🚀 Feature request
I'd like to add `sampling_transform` callback argument to all `generate` functions in `modeling_utils` that allows arbitrary sampling from the probability distribution during sequence generation. The signature of this function would be `(input_ids, next_probs, next_token) -> next_token`.
## Mot... | {
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## Information
Model I am using (Bert, XLNet ...):
Camembert
Language I am using the model on (English, Chinese ...):
French
The problem arises when using:
* [x] the official example scripts: (give details below)
* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
... | {
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"I think in your case it might make more sense to use the `TextGenerationPipeline`. It's a two liner that does the same as the script. You can wrap a `open(inpt_text_file)` and `file.write()` around these two lines in your use case. \r\n\r\nSee documentation for the generation pipeline here: https://huggingface.co/... | 1,588 | 1,591 | 1,591 | NONE | null | Example:
python3 examples/run_generation.py --model_type=gpt2 --model_name_or_path="models/custom-774M" --length=400 < test.txt > test_gpt2_400.txt
Version 2.0.3 and earlier accepts a simple linux redirect < test.txt and reads the file line-by-line while generating the corresponding output to > test_gpt2_400_out.... | {
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[ ] update/subclass `MarianTokenizer`
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https://api.github.com/repos/huggingface/transformers/issues/4159 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4159/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4159/comments | https://api.github.com/repos/huggingface/transformers/issues/4159/events | https://github.com/huggingface/transformers/pull/4159 | 612,780,029 | MDExOlB1bGxSZXF1ZXN0NDEzNjYwMDg1 | 4,159 | Tokenizer.batch_decode convenience method | {
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https://api.github.com/repos/huggingface/transformers/issues/4158 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4158/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4158/comments | https://api.github.com/repos/huggingface/transformers/issues/4158/events | https://github.com/huggingface/transformers/issues/4158 | 612,773,264 | MDU6SXNzdWU2MTI3NzMyNjQ= | 4,158 | [Marian] @-@ symbol causes strange generations | {
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"This is only an issue for BPE models, which we are not supporting."
] | 1,588 | 1,589 | 1,589 | CONTRIBUTOR | null | good fr-en test case:
```
Veuillez m' apporter une demi @-@ bouteille de vin .
``` | {
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https://api.github.com/repos/huggingface/transformers/issues/4157 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4157/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4157/comments | https://api.github.com/repos/huggingface/transformers/issues/4157/events | https://github.com/huggingface/transformers/issues/4157 | 612,772,673 | MDU6SXNzdWU2MTI3NzI2NzM= | 4,157 | [Marian] Readme parser defaults to porting oldest model | {
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"Not true, fixed on master."
] | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | - logic should be newest model or all models with unique names.
- the download URL (and probably other metadata) should be put in a `model_cards/` file.
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"Could you please tell what does this mean ?\r\n```\r\n#!/bin/bash -eo pipefail\r\nblack --check --line-length 119 --target-version py35 examples templates tests src utils\r\n\r\nwould reformat /home/circleci/transformers/examples/pplm/run_pplm.py\r\nOh no! 💥 💔 💥\r\n1 file would be reformatted, 266 files would b... | 1,588 | 1,590 | 1,590 | CONTRIBUTOR | null | {
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"Hi, did you find out the reason for this error? I get the same error even on Wikitext-2 corpus ",
"Yeah, it is an issue with how your data is read. Try the --line_by_line argument. "
] | 1,588 | 1,589 | 1,588 | NONE | null | When training the "run_language_modelling.py" example with a pretrained bert model, I get the error:
"""
Traceback (most recent call last): ... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4154?src=pr&el=h1) Report\n> Merging [#4154](https://codecov.io/gh/huggingface/transformers/pull/4154?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/818463ee8eaf3a1cd5ddc2623789cbd7bb517d02&el=desc) will **increase... | 1,588 | 1,588 | 1,588 | MEMBER | null | Batch support in Pipeline was confusing and not well tested.
This PR rewrites all the content of `DefaultArgumentHandler` which handles most of the input conversions (args, kwargs, batched, etc.) and brings unit tests on this specific class.
Signed-off-by: Morgan Funtowicz <morgan@huggingface.co> | {
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"I am running into the same error on my own script. Interestingly it only appears on CPU... Did you find a solution?",
"No, I want to get a French Q&A pipeline, surprinsingly, with the hugging face pipeline everything works great, I can plug the code in a local server and make requests on it. \r\n\r\nBut when I t... | 1,588 | 1,591 | 1,589 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):
Camembert
Language I am using the model on (English, Chinese ...):
French
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on ... | {
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"### Screenshots of Documentation\r\n\r\n\r\n\r\n\r\n[ x] Shows up in TOC:\r\n:
- ... | {
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"We still need to provide a good docstring/notebook for this. It's on our ToDo-List. :-) \r\n\r\nOr @sshleifer - is there already something for Bart? ",
"Nothing yet, would be good to add!",
"This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no furthe... | 1,588 | 1,678 | 1,602 | NONE | null | How to pre-train BART model in an unsupervised manner. any example? | {
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"You get the default config file as written on AWS with \r\n```python \r\nconfig = T5Config.from_pretrained(\"t5-small\")\r\n```\r\n\r\nIf you want to change anything on the config after you can update it with a dict of your specifications:\r\n```python \r\nconfig.update(your_dict)\r\n```",
"Hello @patrickvonplat... | 1,588 | 1,622 | 1,588 | NONE | null | # ❓ Questions & Help
<!-- The GitHub issue tracker is primarly intended for bugs, feature requests,
new models and benchmarks, and migration questions. For all other questions,
we direct you to Stack Overflow (SO) where a whole community of PyTorch and
Tensorflow enthusiast can help you out. Make s... | {
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https://api.github.com/repos/huggingface/transformers/issues/4149 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4149/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4149/comments | https://api.github.com/repos/huggingface/transformers/issues/4149/events | https://github.com/huggingface/transformers/issues/4149 | 612,255,996 | MDU6SXNzdWU2MTIyNTU5OTY= | 4,149 | Fine-tuning T5 in Tensorflow | {
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"Hi @tqdo, \r\n\r\nGood question. We will add better explanation for TF T5 soon :-) ",
"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",
"@tqdo. I open sourced fine-tuning T5 by custom... | 1,588 | 1,605 | 1,605 | NONE | null | I wonder whether there is an example/tutorial about how to fine-tune T5 for a particular task (say translation) in Tensorflow. On the doc website it says that `This model is a tf.keras.Model tf.keras.Model sub-class`. However I am not really sure what the output is for the Keras model. It seems like the output (the tar... | {
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https://api.github.com/repos/huggingface/transformers/issues/4148 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4148/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4148/comments | https://api.github.com/repos/huggingface/transformers/issues/4148/events | https://github.com/huggingface/transformers/issues/4148 | 612,231,472 | MDU6SXNzdWU2MTIyMzE0NzI= | 4,148 | DistilBertForQuestionAnswering returns [UNK] | {
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"Solved : Had to update transformers & torch\r\nthis code is working fine :\r\n```python\r\nfrom transformers import DistilBertTokenizer, DistilBertForQuestionAnswering\r\nimport torch\r\n\r\ntokenizer = DistilBertTokenizer.from_pretrained(\r\n 'distilbert-base-uncased-distilled-squad')\r\nmodel = DistilBertForQ... | 1,588 | 1,588 | 1,588 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):Distilbert
Language I am using the model on (English, Chinese ...):English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [X] my own modified scripts: (give details below)
The tasks I am working on is:... | {
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"The longest input length a pretrained GPT2 model can treat depends on its `n_position` value. You can look it up here e.g. https://s3.amazonaws.com/models.huggingface.co/bert/gpt2-config.json . \r\nIf you use a pretrained-model you sadly can only treat sequences <= 1024.\r\n\r\nFor you own model you can increase `... | 1,588 | 1,591 | 1,591 | NONE | null | Hi,
I am using a following code to calculate the perplexity of sentences on my GPT-2 pretrained model:
```
tokenizer = GPT2Tokenizer.from_pretrained('gpt-model')
config = GPT2Config.from_pretrained('gpt-model')
model = GPT2LMHeadModel.from_pretrained('gpt-model', config=config)
... | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4146?src=pr&el=h1) Report\n> Merging [#4146](https://codecov.io/gh/huggingface/transformers/pull/4146?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d713cfc5ebfb1ed83de1fce55dd7279f9db30672&el=desc) will **decrease... | 1,588 | 1,588 | 1,588 | MEMBER | null | This PR aims to bring TPU support to the trainer. It runs on GLUE/MRPC but is yet untested on others.
Left to do:
- [ ] Saving and reloading mid-training
- [ ] Check it runs on a few examples (Language modeling, NER, other GLUE tasks)
- [ ] Write down training speed-ups
- [ ] Write down evaluation speed-ups
... | {
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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"
] | 1,588 | 1,594 | 1,594 | CONTRIBUTOR | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
```
batch_tokens = self.tokenizer.batch_encode_plus(
[example.text_a for example in examples],
max_length=max_seq_len,
... | {
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"If you used pytorch-lightning for training then you can load the weights from checkpoint as follows\r\n```\r\nckpt = torch.load('./bart_sum/checkpointepoch=2.ckpt')\r\nmodel.load_state_dict(ckpt['state_dict'])\r\n```\r\n\r\nonce you load the weights this way then save the model using the `.save_pretrained` method ... | 1,588 | 1,639 | 1,592 | NONE | null | Hi
I am using a slightly old tag of ur repo where BART had run_bart_sum.py. I finetuned bart-large on a custom data set and want to do conditional generation
```
from transformers import BartTokenizer, BartForConditionalGeneration
import torch
model = BartForConditionalGeneration.from_pretrained('bart-large'... | {
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https://api.github.com/repos/huggingface/transformers/issues/4142 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4142/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4142/comments | https://api.github.com/repos/huggingface/transformers/issues/4142/events | https://github.com/huggingface/transformers/issues/4142 | 611,674,051 | MDU6SXNzdWU2MTE2NzQwNTE= | 4,142 | New model addition: Blender (Facebook chatbot) | {
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"@tx1985 awesome idea",
"Very Cool !",
"+1",
"Hey, \r\nI want to ask a question regarding Facebook Blender Chatbot. I want to train my custom data into blender. how can i do that? Please help",
"Sorry, I know how to use blender as is but not how to fine tune it. I\nthink that you would require a significa... | 1,588 | 1,598 | 1,598 | NONE | null | # 🌟 New model addition
## Model description
- Dialogue response generation model for multiturn conversations, open-sourced by Facebook (28 April 2020)
- 3 models: 90m, 2.7b and 9.4b parameters
- New state-of-the-art "in terms of engagingness and humanness measurements"
- Blog post: https://parl.ai/projects/blen... | {
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"I agree! Do you want to open a PR about this to change the naming? :-) \r\nWhen doing this we just have to be careful to not change the user facing api when doing this -> which means that ideally, we should not rename any function arguments of high level modules like `BertModel.forward()`.",
"I've created PR #45... | 1,588 | 1,595 | 1,595 | NONE | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
## Motivation
I noticed that some users are pretty confused when reading source codes about variable `attention_mask`
like:
[What is the meaning of Attent... | {
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https://api.github.com/repos/huggingface/transformers/issues/4140 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4140/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4140/comments | https://api.github.com/repos/huggingface/transformers/issues/4140/events | https://github.com/huggingface/transformers/issues/4140 | 611,636,973 | MDU6SXNzdWU2MTE2MzY5NzM= | 4,140 | How to make run_language_modeling.py work for transformer-xl? | {
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"Yeah we don't have a run_language_modeling.py script yet. It's on a TODO list :-). Also see: #2008 .\r\nIf you feel like writing one, it would be great :-) "
] | 1,588 | 1,591 | 1,591 | NONE | null | The code in [run_language_modeling.py](https://github.com/huggingface/transformers/blob/master/examples/run_language_modeling.py) does Language modeling for any pre-trained model. However, for transformer-xl, we need additional arguments to the forward function like `mems` and even [run_transfo_xl.py](https://github.co... | {
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"IMO the docstring is confusing here. This PR should fix it: #4422. \r\n& You are right you should change `max_position_embeddings` via `n_positions`."
] | 1,588 | 1,589 | 1,589 | NONE | null | # 🐛 Bug
## Information
The model I am using (T5):
Language I am using the model on (English):
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
```
config = T5Config(max_position_embeddings=1024)
```
## To r... | {
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https://api.github.com/repos/huggingface/transformers/issues/4138 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4138/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4138/comments | https://api.github.com/repos/huggingface/transformers/issues/4138/events | https://github.com/huggingface/transformers/pull/4138 | 611,544,377 | MDExOlB1bGxSZXF1ZXN0NDEyNjkyNjE0 | 4,138 | [Roberta] fix hard wired pad token id | {
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"I checked all models on `https://huggingface.co/models?search=roberta` and all of them have the pad_token_id set to `1` which was used as a default before. So this is good to merge for me."
] | 1,588 | 1,588 | 1,588 | MEMBER | null | This might break backward compatibility for users that have uploaded a roberta model and use a different pad token than 1 in the configs.
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https://api.github.com/repos/huggingface/transformers/issues/4137 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4137/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4137/comments | https://api.github.com/repos/huggingface/transformers/issues/4137/events | https://github.com/huggingface/transformers/issues/4137 | 611,504,515 | MDU6SXNzdWU2MTE1MDQ1MTU= | 4,137 | Error: `cannot import name 'TFBertForMaskedLM'` | {
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"The issue was that I did not have TensorFlow installed. "
] | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | When I try the following import:
```python
from transformers import TFBertForMaskedLM
```
I get the following error:
```
Traceback (most recent call last):
File "/Users/danielk/ideaProjects/farsi-language-models/src/try_bert_lm.py", line 3, in <module>
from transformers import TFBertForMaskedLM
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https://api.github.com/repos/huggingface/transformers/issues/4136 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4136/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4136/comments | https://api.github.com/repos/huggingface/transformers/issues/4136/events | https://github.com/huggingface/transformers/issues/4136 | 611,497,873 | MDU6SXNzdWU2MTE0OTc4NzM= | 4,136 | Cannot loading SpanBERT pre-trained model | {
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"@palooney \r\nCan you check again ?. The following call worked for me\r\n```\r\nmodel = AutoModel.from_pretrained(\"SpanBERT/spanbert-base-cased\")\r\n```",
"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 yo... | 1,588 | 1,594 | 1,594 | NONE | null | I have some questions regarding SpanBert loading using the transformers package.
I downloaded the pre-trained file from [SpanBert](https://github.com/facebookresearch/SpanBERT) GitHub Repo and ```vocab.txt``` from Bert. Here is the code I used for loading:
```python
model = BertModel.from_pretrained(config_file=... | {
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https://api.github.com/repos/huggingface/transformers/issues/4135 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4135/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4135/comments | https://api.github.com/repos/huggingface/transformers/issues/4135/events | https://github.com/huggingface/transformers/issues/4135 | 611,487,504 | MDU6SXNzdWU2MTE0ODc1MDQ= | 4,135 | Why does ALBERT use einsum in PyTorch implementation while in TF one it does not? | {
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"The two implementations are equivalent, but the Pytorch version is cumbersome.\r\nI think the code\r\n\r\n```python\r\n context_layer = context_layer.permute(0, 2, 1, 3).contiguous()\r\n\r\n # Should find a better way to do this\r\n w = (\r\n self.dense.weight.t()\r\n ... | 1,588 | 1,602 | 1,602 | CONTRIBUTOR | null | # ❓ Questions & Help
I wanted to learn internals of ALBERT model from your implementation (which is BTW really clean in comparison to the original one - good job!), but I've stumbled upon weird looking part in the `AlbertAttention`: https://github.com/huggingface/transformers/blob/6af3306a1da0322f58861b1fbb62ce5223d97... | {
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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",
"same here, mine is torch version, though.\r\n@mobassir94 Did you fix it?",
"@HenryPaik1 no\r\ni also faced this issue in both pytorch... | 1,588 | 1,611 | 1,594 | NONE | null | # 🐛 jplu/tf-xlm-roberta-large showing random performance on tpu model training
## i have observed several times that jplu/tf-xlm-roberta-large showing random performance on several experiments,for example if i train a model and get validation accuracy 61% then if i run the model again (without changing anythin or d... | {
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https://api.github.com/repos/huggingface/transformers/issues/4133 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4133/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4133/comments | https://api.github.com/repos/huggingface/transformers/issues/4133/events | https://github.com/huggingface/transformers/issues/4133 | 611,443,102 | MDU6SXNzdWU2MTE0NDMxMDI= | 4,133 | problem about change from pytorch-pretrained-bert to transformers | {
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"OK, the problem is, in transformers, forward() method args position is little bit different compare to pytorch-pretrained-bert. the order change from (token, segment, mask) to (token, mask, segment). So pass the args by name will always right, lol"
] | 1,588 | 1,588 | 1,588 | NONE | null | I am doing the sentiment analysis with pytorch-pretrained-bert, it work correct, but when I change to transformers, the accuracy on the dev data is poor (but the accuracy with pytorch-pretrained-bert is quite higher). Besides, I notice the Migrating from pytorch-pretrained-bert to transformers module.
the input is:
[... | {
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https://api.github.com/repos/huggingface/transformers/issues/4132 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4132/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4132/comments | https://api.github.com/repos/huggingface/transformers/issues/4132/events | https://github.com/huggingface/transformers/pull/4132 | 611,400,627 | MDExOlB1bGxSZXF1ZXN0NDEyNTk0MTEx | 4,132 | Create README.md | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4132?src=pr&el=h1) Report\n> Merging [#4132](https://codecov.io/gh/huggingface/transformers/pull/4132?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/6af3306a1da0322f58861b1fbb62ce5223d97b8a&el=desc) will **increase... | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4131 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4131/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4131/comments | https://api.github.com/repos/huggingface/transformers/issues/4131/events | https://github.com/huggingface/transformers/pull/4131 | 611,376,443 | MDExOlB1bGxSZXF1ZXN0NDEyNTc4Njc2 | 4,131 | Make transformers-cli cross-platform | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4131?src=pr&el=h1) Report\n> Merging [#4131](https://codecov.io/gh/huggingface/transformers/pull/4131?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1cdd2ad2afb73f6af185aafecb7dd7941a90c4d1&el=desc) will **decrease... | 1,588 | 1,590 | 1,590 | COLLABORATOR | null | Using `scripts` is a useful option in `setup.py` particularly when you want to get access to non-python scripts. However, in this case we want to have an entry point into some of our own Python scripts. To do this in a concise, cross-platfom way, we can use `entry_points.console_scripts`. This change is necessary to pr... | {
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https://api.github.com/repos/huggingface/transformers/issues/4130 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4130/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4130/comments | https://api.github.com/repos/huggingface/transformers/issues/4130/events | https://github.com/huggingface/transformers/issues/4130 | 611,354,140 | MDU6SXNzdWU2MTEzNTQxNDA= | 4,130 | GPT-2 past behaves incorrectly when attention_mask is used | {
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"Solved. `attention_mask ` should be the full tensor (not just the last step), even when `past` is used."
] | 1,588 | 1,588 | 1,588 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): GPT-2
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
The tasks I am working on is:
*... | {
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https://api.github.com/repos/huggingface/transformers/issues/4129 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4129/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4129/comments | https://api.github.com/repos/huggingface/transformers/issues/4129/events | https://github.com/huggingface/transformers/issues/4129 | 611,334,490 | MDU6SXNzdWU2MTEzMzQ0OTA= | 4,129 | Parse in tensorflow strings as well as normal strings | {
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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",
"Hey, any updates about this issue? I'm facing the exact same problem!",
"@sachinruk @joaopedromattos any luck here in the end :)"
] | 1,588 | 1,646 | 1,594 | CONTRIBUTOR | null | # 🚀 Feature request
So this is something I came across while trying to get a (fast) streaming dataset via the tensorflow data API for TPUs. This is a crosspost of [this SO question](https://stackoverflow.com/questions/61555097/mapping-text-data-through-huggingface-tokenizer/).
I have my encode function that looks... | {
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https://api.github.com/repos/huggingface/transformers/issues/4128 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4128/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4128/comments | https://api.github.com/repos/huggingface/transformers/issues/4128/events | https://github.com/huggingface/transformers/pull/4128 | 611,324,049 | MDExOlB1bGxSZXF1ZXN0NDEyNTQyNzI2 | 4,128 | Add decoder specific error message for T5Stack.forward | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4128?src=pr&el=h1) Report\n> Merging [#4128](https://codecov.io/gh/huggingface/transformers/pull/4128?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1cdd2ad2afb73f6af185aafecb7dd7941a90c4d1&el=desc) will **decrease... | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | #### This PR adds a decoder specific error message in `T5Stack.forward` in the case that `self.is_decoder == True`
This was requested in #4126 and suggested by @patrickvonplaten in #3626 .
Confirmed that this works as expected in this colab [notebook](https://colab.research.google.com/drive/1j1mdtOylXZClH-ikZthDi... | {
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https://api.github.com/repos/huggingface/transformers/issues/4127 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4127/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4127/comments | https://api.github.com/repos/huggingface/transformers/issues/4127/events | https://github.com/huggingface/transformers/issues/4127 | 611,323,721 | MDU6SXNzdWU2MTEzMjM3MjE= | 4,127 | Model output should be dict | {
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"We will soon convert the outputs of models to named tuples to that it will be more readable :-) "
] | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | # 🚀 Feature request
<!-- A clear and concise description of the feature proposal.
Please provide a link to the paper and code in case they exist. -->
I think model output should be a dict. Since dict are more clearly than tuple, we do not know what output[1] means, but we do know output["pooled_ouptut"] mean... | {
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https://api.github.com/repos/huggingface/transformers/issues/4126 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4126/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4126/comments | https://api.github.com/repos/huggingface/transformers/issues/4126/events | https://github.com/huggingface/transformers/issues/4126 | 611,322,660 | MDU6SXNzdWU2MTEzMjI2NjA= | 4,126 | No decoder specific error message for T5Stack.forward | {
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`ValueError: You have to specify either input_ids or inputs_embeds`
I've confirmed with @patrickvonplaten that it makes... | {
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https://api.github.com/repos/huggingface/transformers/issues/4125 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4125/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4125/comments | https://api.github.com/repos/huggingface/transformers/issues/4125/events | https://github.com/huggingface/transformers/issues/4125 | 611,294,182 | MDU6SXNzdWU2MTEyOTQxODI= | 4,125 | Is it possible to have high perplexity of some individual sentences, as compared to overall testing corpus perplexity? | {
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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"
] | 1,588 | 1,594 | 1,594 | NONE | null | Hi,
I have calculated an overall perplexity of my testing corpus after finetuning GPT-2 pretrained model
Similarly, I have also calculated perplexity of individual sentences, after extracting it from my testing corpus.
**I notice that some individual sentence perplexity is even higher than the overall perplexity... | {
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https://api.github.com/repos/huggingface/transformers/issues/4124 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4124/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4124/comments | https://api.github.com/repos/huggingface/transformers/issues/4124/events | https://github.com/huggingface/transformers/issues/4124 | 611,258,268 | MDU6SXNzdWU2MTEyNTgyNjg= | 4,124 | convert pytorch_model.pt [pretrained Bert model] to pytorch_model.onnx (ONNX) | {
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"May be of interest to @mfuntowicz ",
"Hi @pumpkinband, \r\n\r\nI don't have the exact details of the model you're trying to load, but I'd assume a tensor of shape (1, 3) would make more sense (batch, sequence). ",
"This issue has been automatically marked as stale because it has not had recent activity. It wil... | 1,588 | 1,595 | 1,595 | NONE | null | i use this to convert pytorch_model.pt to pytorch_model.onnx
```
from torch.autograd import Variable
import torch.onnx
import torchvision
import torch
dummy_input = Variable(torch.randn(1, 3, 256, 256))
model = torch.load('./pytorch_model.pt')
torch.onnx.export(model, dummy_input, "pytorch_model.onnx")
```... | {
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https://api.github.com/repos/huggingface/transformers/issues/4123 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4123/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4123/comments | https://api.github.com/repos/huggingface/transformers/issues/4123/events | https://github.com/huggingface/transformers/pull/4123 | 611,250,481 | MDExOlB1bGxSZXF1ZXN0NDEyNDkxODkz | 4,123 | Text corrections | {
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"@lapolonio - thanks a lot for these fixes. I already applied them in the main PR :-) "
] | 1,588 | 1,588 | 1,588 | NONE | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4122 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4122/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4122/comments | https://api.github.com/repos/huggingface/transformers/issues/4122/events | https://github.com/huggingface/transformers/issues/4122 | 611,237,350 | MDU6SXNzdWU2MTEyMzczNTA= | 4,122 | ValueError: You are attempting to pad samples but the tokenizer you are using (GPT2Tokenizer) does not have one. | {
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"I had the same error; I think the problem lies in \"line_by_line\" since if I remove this option, my code can run fine.",
"@BramVanroy - sorry to just link you here. Did we decide to add a force-padding option here or not yet? ",
"We had the discussion over here https://github.com/huggingface/transformers/pull... | 1,588 | 1,614 | 1,609 | NONE | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...):GPT2
Language I am using the model on (English, Chinese ...):English
The problem arises when using:
my own modified scripts: (give details below)
python examples/run_language_modeling.py \
--train_data_file=temp_gpt2/gpt2.train \
--out... | {
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"Hi @girishponkiya,\r\n\r\nThanks for the detailed error description. I was not able to reproduce the error with the newest version of transformers, 2.9.0.\r\n\r\nSee google colab here: https://colab.research.google.com/drive/14TQzMBPuaNb6aZ_NoVFQrr_ZTJS2mCr3 . Can you check again with a newer version of transforme... | 1,588 | 1,591 | 1,591 | CONTRIBUTOR | null | # 🐛 Bug
## Information
Model I am using (Bert, XLNet ...): `T5ForConditionalGeneration`
Language I am using the model on (English, Chinese ...): English
The problem arises when using:
* [ ] the official example scripts: (give details below)
* [x] my own modified scripts: (give details below)
```python... | {
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https://api.github.com/repos/huggingface/transformers/issues/4120 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4120/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4120/comments | https://api.github.com/repos/huggingface/transformers/issues/4120/events | https://github.com/huggingface/transformers/pull/4120 | 611,215,138 | MDExOlB1bGxSZXF1ZXN0NDEyNDY3OTc1 | 4,120 | fixed utils_summarization import path | {
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"I think you need to run `make style` and resolve merge conflicts.\r\n",
"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"
] | 1,588 | 1,599 | 1,599 | NONE | null | As per issue #3827 I've removed the dot in the import. | {
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https://api.github.com/repos/huggingface/transformers/issues/4119 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4119/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4119/comments | https://api.github.com/repos/huggingface/transformers/issues/4119/events | https://github.com/huggingface/transformers/pull/4119 | 611,214,398 | MDExOlB1bGxSZXF1ZXN0NDEyNDY3NTA4 | 4,119 | Fix markdown to show the results table properly | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4119?src=pr&el=h1) Report\n> Merging [#4119](https://codecov.io/gh/huggingface/transformers/pull/4119?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/1cdd2ad2afb73f6af185aafecb7dd7941a90c4d1&el=desc) will **decrease... | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4118 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4118/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4118/comments | https://api.github.com/repos/huggingface/transformers/issues/4118/events | https://github.com/huggingface/transformers/pull/4118 | 611,189,690 | MDExOlB1bGxSZXF1ZXN0NDEyNDUxNjEw | 4,118 | Update run_pl_ner.py | {
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"Thanks @williamFalcon – do we need to bump the minimal version of `pytorch-lightning` then?",
"We're backward compatible, so no need to bump but 0.7.5 has forward support for native amp and solves a few key bugs that were present in earlier versions. I would recommend bumping up."
] | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4117 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4117/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4117/comments | https://api.github.com/repos/huggingface/transformers/issues/4117/events | https://github.com/huggingface/transformers/pull/4117 | 611,189,483 | MDExOlB1bGxSZXF1ZXN0NDEyNDUxNDg2 | 4,117 | Update run_pl_glue.py | {
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"Same question as https://github.com/huggingface/transformers/pull/4118#issuecomment-622963241"
] | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/transformers/issues/4116 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4116/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4116/comments | https://api.github.com/repos/huggingface/transformers/issues/4116/events | https://github.com/huggingface/transformers/pull/4116 | 611,182,351 | MDExOlB1bGxSZXF1ZXN0NDEyNDQ3NjE4 | 4,116 | Updated | {
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https://api.github.com/repos/huggingface/transformers/issues/4115 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4115/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4115/comments | https://api.github.com/repos/huggingface/transformers/issues/4115/events | https://github.com/huggingface/transformers/pull/4115 | 611,164,305 | MDExOlB1bGxSZXF1ZXN0NDEyNDM3NTg2 | 4,115 | Create model card | {
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"Great!",
"You do not rest even on Saturday! 🦾"
] | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | Create Model card for distilroberta-base-finetuned-sentiment | {
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https://api.github.com/repos/huggingface/transformers/issues/4114 | https://api.github.com/repos/huggingface/transformers | https://api.github.com/repos/huggingface/transformers/issues/4114/labels{/name} | https://api.github.com/repos/huggingface/transformers/issues/4114/comments | https://api.github.com/repos/huggingface/transformers/issues/4114/events | https://github.com/huggingface/transformers/pull/4114 | 611,158,856 | MDExOlB1bGxSZXF1ZXN0NDEyNDM0MDQw | 4,114 | model card for surajp/albert-base-sanskrit | {
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"# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4114?src=pr&el=h1) Report\n> Merging [#4114](https://codecov.io/gh/huggingface/transformers/pull/4114?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/abb1fa3f374811ea09d0bc3440d820c50735008d&el=desc) will **not chan... | 1,588 | 1,588 | 1,588 | CONTRIBUTOR | null | Added Model card for `surajp/albert-base-sanskrit` | {
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