noamaanMulla-03/transformers-issues huggingface dataset:
Add model card for StackOBERTflow-comments-small
Author: furunkel
Pull request: yes
Labels: name: model card


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5008?src=pr&el=h1) Report
> Merging [#5008](https://codecov.io/gh/huggingface/transformers/pull/5008?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ebab096e864a619717a497089d864d10e21bc536&el=desc) will **increase** coverage by `0.39%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5008/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5008?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5008      +/-   ##
==========================================
+ Coverage   77.26%   77.66%   +0.39%     
==========================================
  Files         128      128              
  Lines       21854    21854              
==========================================
+ Hits        16886    16973      +87     
+ Misses       4968     4881      -87     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5008?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/file\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5008/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.38% <0.00%> (-0.41%)` | :arrow_down: |
| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/5008/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `56.68% <0.00%> (+28.02%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5008?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5008?src=pr&el=footer). Last update [ebab096...bd9e483](https://codecov.io/gh/huggingface/transformers/pull/5008?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
Create README.md for finetuned BERT model
Author: fran-martinez
Pull request: yes
Labels: name: model card


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5009?src=pr&el=h1) Report
> Merging [#5009](https://codecov.io/gh/huggingface/transformers/pull/5009?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/ebab096e864a619717a497089d864d10e21bc536&el=desc) will **increase** coverage by `0.06%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5009/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5009?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5009      +/-   ##
==========================================
+ Coverage   77.26%   77.33%   +0.06%     
==========================================
  Files         128      128              
  Lines       21854    21854              
==========================================
+ Hits        16886    16900      +14     
+ Misses       4968     4954      -14     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5009?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/file\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5009/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.38% <0.00%> (-0.41%)` | :arrow_down: |
| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/5009/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `39.25% <0.00%> (-0.24%)` | :arrow_down: |
| [src/transformers/modeling\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5009/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.61% <0.00%> (+0.11%)` | :arrow_up: |
| [src/transformers/data/processors/squad.py](https://codecov.io/gh/huggingface/transformers/pull/5009/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9kYXRhL3Byb2Nlc3NvcnMvc3F1YWQucHk=) | `33.43% <0.00%> (+4.77%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5009?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5009?src=pr&el=footer). Last update [ebab096...97c4e50](https://codecov.io/gh/huggingface/transformers/pull/5009?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
test_resize_tokens_embeddings does not inspect `get_output_embeddings`
Author: sshleifer
Pull request: no
Labels: name: Help wanted

name: wontfix

Here is the existing logic: copied below for convenience
https://github.com/huggingface/transformers/blob/bbf26c4e619cf42106163e1e2cd5ff98b936ff93/tests/test_modeling_common.py#L489)

```python
model_embed = model.resize_token_embeddings(config.vocab_size)
cloned_embeddings = model_embed.weight.clone()
# Check that resizing the token embeddings with a larger vocab size increases the model's vocab size
model_embed = model.resize_token_embeddings(model_vocab_size + 10)
self.assertEqual(model.config.vocab_size, model_vocab_size + 10)
self.assertEqual(model_embed.weight.shape[0], cloned_embeddings.shape[0] + 10)
```

Since we never test the return value of `get_output_embeddings` after resizing, the model can avoid setting it to the new vocab size. 
BART did this by overwriting `tie_weights` to do nothing (fix proposed in https://github.com/huggingface/transformers/pull/3323)




Comments:
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.
Error when using run_generation.py to generate texts with long prompts, specifically for models -XLM and Openai-GPT
Author: AdaUchendu
Pull request: no
Labels: name: wontfix

# 🐛 Bug

## Information

Model I am using (XLM, OPENAI-GPT):

Language I am using the model on (English):

The problem arises when using:
* [ ] The models to generate texts with long prompts 

The tasks I am working on is:
* [ ] Text generation

## To reproduce

Steps to reproduce the behavior:

1. cd transformers/
python examples/run_generation.py  --model_type xlm --model_name_or_path xlm-mlm-en-2048 \
                                  --prompt "China wants to take a victory lap over its handling of the coronavirus outbreak" \
                                  --repetition 2.2 --k 5 \
                                  --length 500 

2. 
3.

<!-- Error:   RuntimeError: The size of tensor a (513) must match the size of tensor b (512) at non-singleton dimension 3. \
This leads to the next error - RuntimeError: CUDA error: device-side assert triggered.-->

## Expected behavior

<!-- The expected behavior is a generated piece of texts of about 500 words -->

## Environment info
<!-- cd transformers/
python examples/run_generation.py  --model_type xlm --model_name_or_path xlm-mlm-en-2048 \
                                  --prompt "China wants to take a victory lap over its handling of the coronavirus outbreak" \
                                  --repetition 2.2 --k 5 \
                                  --length 500  -->
     
I think the problem is that there is a bug somewhere in the input_embed or input_id or vocabulary because seems to out of index given certain prompts. This may suggest that the vocab list is limited or maybe not. 

- `transformers` version:
- Platform: Google Colab 
- Python version: 3.6.9
- PyTorch version (GPU?): 1.4.0
- Tensorflow version (GPU?): no
- Using GPU in script?: yes
- Using distributed or parallel set-up in script?: no


Comments:
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.
how to get complete URLs to weights in 2.11.0
Author: allanj
Pull request: no

# ❓ Questions & Help

Since it is related to the newest release, I would like to raise the question here. As our servers in the company are not able to access the HF url, we have to download the models locally and upload to the servers. Now seems I couldn't find the links to download `pytorch_model.bin`, `config.json`, `vocab.json`, `merge.txt`. 

The only one I can find is https://huggingface.co/facebook/bart-large

But  it only shows:

| File name | Last modified | File size|
|-- | -- | --|
|config.json | Fri, 24 Apr 2020 15:58:48 GMT | 1.2KB|
|pytorch_model.bin | Wed, 12 Feb 2020 19:53:45 GMT | 1.5GB|
|rust_model.ot | Sat, 25 Apr 2020 15:33:01 GMT | 1.9GB|

There is no `vocab.json`, `merge.txt`.  I want to find the complete URLs to these files.




Comments:
They are the same as Roberta's 

```python
vocab_url = "https://s3.amazonaws.com/models.huggingface.co/bert/roberta-large-vocab.json"
merges_url = "https://s3.amazonaws.com/models.huggingface.co/bert/roberta-large-merges.txt"
```

Is your question more general than just `bart-large`? (Feel free to close if not :) )

Thanks and yes. I'm interested in a more general case to retrieve the URLs to weights for different models.
Currently, what I did actually is switching back to 2.10.0. And go to corresponding `modeling_xxx.py` and find the download link.

You can find URLs to specific files on each model page (click on "List all files"): https://huggingface.co/distilbert-base-cased#list-files

Hi @julien-c , as mentioned, I actually know this way, but "list all files" seems not giving me the `vocab.json`, `merge.txt`, OR are they not required? 

Not all tokenizer types use those files. For instance Wordpiece (e.g. bert) is just one vocab.txt file.

Yup. I understand that, just named an example. But just want to make sure that files in https://huggingface.co/distilbert-base-cased#list-files are sufficient for me to use.
[Modelcard] xlm-roberta-squadv2
Author: flozi00
Pull request: yes
Labels: name: model card


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5013?src=pr&el=h1) Report
> Merging [#5013](https://codecov.io/gh/huggingface/transformers/pull/5013?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/f7c93b3ceec341c3c794e9fc18939bc5d50b0fc2&el=desc) will **increase** coverage by `0.00%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5013/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5013?src=pr&el=tree)

```diff
@@           Coverage Diff           @@
##           master    #5013   +/-   ##
=======================================
  Coverage   77.26%   77.26%           
=======================================
  Files         128      128           
  Lines       21856    21856           
=======================================
+ Hits        16887    16888    +1     
+ Misses       4969     4968    -1     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5013?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5013/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.42% <0.00%> (+0.15%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5013?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5013?src=pr&el=footer). Last update [f7c93b3...ca606b8](https://codecov.io/gh/huggingface/transformers/pull/5013?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
[Modelcard] bart-squadv2
Author: flozi00
Pull request: yes
Labels: name: model card


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5011?src=pr&el=h1) Report
> Merging [#5011](https://codecov.io/gh/huggingface/transformers/pull/5011?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/66bcfbb130a3a60d873597fdca05a8d539ef3401&el=desc) will **increase** coverage by `0.05%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5011/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5011?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5011      +/-   ##
==========================================
+ Coverage   77.20%   77.26%   +0.05%     
==========================================
  Files         128      128              
  Lines       21854    21854              
==========================================
+ Hits        16873    16885      +12     
+ Misses       4981     4969      -12     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5011?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/file\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5011/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `73.38% <0.00%> (-0.41%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5011/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `87.26% <0.00%> (-0.16%)` | :arrow_down: |
| [src/transformers/modeling\_xlnet.py](https://codecov.io/gh/huggingface/transformers/pull/5011/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ194bG5ldC5weQ==) | `78.65% <0.00%> (+2.29%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5011?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5011?src=pr&el=footer). Last update [66bcfbb...19b3655](https://codecov.io/gh/huggingface/transformers/pull/5011?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).


Hi @flozi00 , this is great ! If possible can you link my original training colab so people can train their own models easily if needed. You can find it [here](https://colab.research.google.com/drive/1I5cK1M_0dLaf5xoewh6swcm5nAInfwHy?usp=sharing) 
Thanks !
Linformer
Author: Laksh1997
Pull request: no
Labels: name: New model

# 🌟 New model addition

## Model description

https://arxiv.org/pdf/2006.04768.pdf

This model is very simple, it just projects the key tensor into a lower dimensional space (e.g k=128) along the sequence axis, then computes attention (seq_len x k), softmax, and matmul with the value tensor (note, the value tensor must also be projected to dimension k along the length dimension).

Could this be added?

## Open source status

Pytorch sketch implementation: https://github.com/tatp22/linformer-pytorch


Comments:
Duplicate #4967
[Reformer] Axial Pos Emb Improve mem usage reformer
Author: patrickvonplaten
Pull request: yes

This PR improves memory usage of Axial Position Encodings by cutting position encodings only to the required length before applying contiguous pytorch operations.

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5209?src=pr&el=h1) Report
> Merging [#5209](https://codecov.io/gh/huggingface/transformers/pull/5209?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/355954ffca798bb81d9db8886e30ce10f11e8a40&el=desc) will **increase** coverage by `0.00%`.
> The diff coverage is `100.00%`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5209/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5209?src=pr&el=tree)

```diff
@@           Coverage Diff           @@
##           master    #5209   +/-   ##
=======================================
  Coverage   77.28%   77.28%           
=======================================
  Files         133      133           
  Lines       22134    22135    +1     
=======================================
+ Hits        17107    17108    +1     
  Misses       5027     5027           
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5209?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_reformer.py](https://codecov.io/gh/huggingface/transformers/pull/5209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19yZWZvcm1lci5weQ==) | `88.21% <100.00%> (+0.01%)` | :arrow_up: |
| [src/transformers/file\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `75.00% <0.00%> (-0.41%)` | :arrow_down: |
| [src/transformers/trainer.py](https://codecov.io/gh/huggingface/transformers/pull/5209/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90cmFpbmVyLnB5) | `39.62% <0.00%> (+0.23%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5209?src=pr&el=continue).
> **Legend** - [Click here to learn more](https://docs.codecov.io/docs/codecov-delta)
> `Δ = absolute <relative> (impact)`, `ø = not affected`, `? = missing data`
> Powered by [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5209?src=pr&el=footer). Last update [355954f...cd443f7](https://codecov.io/gh/huggingface/transformers/pull/5209?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
BertForMaskedLM "labels" is an unexpected keyword
Author: guoxuxu
Pull request: no

# 🐛 Bug

## Information

The official BertForMaskedLM example: https://huggingface.co/transformers/model_doc/bert.html#bertformaskedlm
 has a bug. When running: outputs = model(input_ids, labels=input_ids), it alerts: TypeError: forward() got an unexpected keyword argument 'labels'

Model I am using (Bert, XLNet ...):
BERT

Language I am using the model on (English, Chinese ...):
English

The problem arises when using:
* [ ] the official example scripts: (give details below)
from transformers import BertTokenizer, BertForMaskedLM
import torch

tokenizer = BertTokenizer.from_pretrained('bert-base-uncased')
model = BertForMaskedLM.from_pretrained('bert-base-uncased')

input_ids = torch.tensor(tokenizer.encode("Hello, my dog is cute", add_special_tokens=True)).unsqueeze(0)  # Batch size 1
outputs = model(input_ids, labels=input_ids)

* [ ] my own modified scripts: (give details below)
The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)

## To reproduce

Steps to reproduce the behavior:

1. https://huggingface.co/transformers/model_doc/bert.html#bertformaskedlm
2.
3.

<!-- If you have code snippets, error messages, stack traces please provide them here as well.
     Important! Use code tags to correctly format your code. See https://help.github.com/en/github/writing-on-github/creating-and-highlighting-code-blocks#syntax-highlighting
     Do not use screenshots, as they are hard to read and (more importantly) don't allow others to copy-and-paste your code.-->

## Expected behavior
should work with labels??
<!-- A clear and concise description of what you would expect to happen. -->

## Environment info
<!-- You can run the command `transformers-cli env` and copy-and-paste its output below.
     Don't forget to fill out the missing fields in that output! -->
     
- `transformers` version: 2.11.0
- Platform: Linux
- Python version: 3.7
- PyTorch version (GPU?): 1.5.1
- Tensorflow version (GPU?): 2.2.0
- Using GPU in script?: yes 
- Using distributed or parallel set-up in script?: no


Comments:
Hi, @guoxuxu , `lm_labels` is changed to `labels` in a recent commit on master. If you are using master then use `labels` otherwise use `lm_labels` 

@sgugger This change is causing a lot of confusion. Would it be a good idea to keep master and release docs separate ?  

This has just been done. The [documentation](https://huggingface.co/transformers/) now shows the latest stable release (v2.11.0) and you have to opt-in to see the [master documentation](https://huggingface.co/transformers/master/).

I'll work on a version selector next.

Thanks @sgugger  !

I think we can close the issue as a result. Please reopen if any problem persists.
How to predict on a batch?
Author: mariusjohan
Pull request: no

# ❓ 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 sure to tag your question with the
     right deep learning framework as well as the huggingface-transformers tag: 
     https://stackoverflow.com/questions/tagged/huggingface-transformers 
     
     If your question wasn't answered after a period of time on Stack Overflow, you
     can always open a question on GitHub. You should then link to the SO question 
     that you posted.
     -->

## Details
<!-- Description of your issue -->

<!-- You should first ask your question on SO, and only if
     you didn't get an answer ask it here on GitHub. -->
**A link to original question on Stack Overflow**:  
[Link](https://stackoverflow.com/questions/62533181/huggingface-transformers-library-predict-in-batches)


Comments:
Cutom tokenizer not loaded in AutoTokenizer
Author: muhammadfahid51
Pull request: no
Labels: name: wontfix

I am training a language model from scratch. I trained **ByteLevelBPETokenizer** and then when I am trying to load this tokenizer using **AutoTokenizer**, it is giving me the following error.

OSError: Model name './MyRobertaConfig/' was not found in tokenizers model name list (bert-base-uncased, bert-large-uncased, bert-base-cased, bert-large-cased, bert-base-multilingual-uncased, bert-base-multilingual-cased, bert-base-chinese, bert-base-german-cased, bert-large-uncased-whole-word-masking, bert-large-cased-whole-word-masking, bert-large-uncased-whole-word-masking-finetuned-squad, bert-large-cased-whole-word-masking-finetuned-squad, bert-base-cased-finetuned-mrpc, bert-base-german-dbmdz-cased, bert-base-german-dbmdz-uncased, bert-base-finnish-cased-v1, bert-base-finnish-uncased-v1, bert-base-dutch-cased). We assumed './MyRobertaConfig/' was a path, a model identifier, or url to a directory containing vocabulary files named ['vocab.txt'] but couldn't find such vocabulary files at this path or url.

I have not added tokenizer_config.json file in config directory, I don't think it should be an issue. Now do I need to migrate or transform my custom tokenizer to make it compatible with transformers tokenizers or what. 

Comments:
If it's a BPETokenizer, you can load it with `RobertaTokenizer.from_pretrained("vocab.json", "merges.json")`

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