noamaanMulla-03/transformers-issues huggingface dataset:
Can't load to predict a reproduced DistilBERT 
Author: learnercat
Pull request: no

How to load and predict a fine tuning DistilBert Multi Classification Model?

Comments:
I have tested reproducing **[Fine Tuning Transformer for MultiClass Text Classification](https://colab.research.google.com/github/abhimishra91/transformers-tutorials/blob/master/transformers_multiclass_classification.ipynb)** successfully. But I tried to load the model and vocab files from a spirited file predict_distilbert.ipynb as below:
`# Importing libraries`
`import pandas as pd`
`import torch`
`import transformers`
`import numpy as np`
`from torch.utils.data import Dataset, DataLoader`
`from transformers import DistilBertModel, DistilBertTokenizer`
`test_string = "The temperature, relative humidity and wind information shown above are the respective forecasts over a 24-hour period."`
`tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-cased','models/vocab_distilbert_news.bin')`
`load_model = DistilBertModel.from_pretrained('distilbert-base-cased','models/pytorch_distilbert_news.bin')`
Then I got "TypeError   --->  Traceback (most recent call last)"
`<ipython-input-17-274a96b92c04> in <module>`
`----> 1 tokenizer = DistilBertTokenizer.from_pretrained('distilbert-base-cased','models/vocab_distilbert_news.bin')`
`2 load_model = DistilBertModel.from_pretrained('distilbert-base-cased','models/pytorch_distilbert_news.bin')`
`~/anaconda3/envs/hgface/lib/python3.7/site-packages/transformers/tokenization_utils.py in from_pretrained(cls, *inputs, **kwargs)`
`--> 911         return cls._from_pretrained(*inputs, **kwargs)`
`912 
    913     @classmethod`
`~/anaconda3/envs/hgface/lib/python3.7/site-packages/transformers/tokenization_utils.py in _from_pretrained(cls, pretrained_model_name_or_path, *init_inputs, **kwargs)`
`1060         # Instantiate tokenizer.`
`1061         try:`
`-> 1062             tokenizer = cls(*init_inputs, **init_kwargs)`
`1063         except OSError:`
`1064             raise OSError(`
`TypeError: __init__() got multiple values for argument 'vocab_file'`

Please help!











# Solved this problem in [Fine tuning DistilBERT model OSError: Unable to load weights from pytorch checkpoint file. #4](https://github.com/abhimishra91/transformers-tutorials/issues/4)
Create README.md - Model card
Author: nreimers
Pull request: yes
Labels: name: model card

Model card for sentence-transformers/bert-base-nli-max-tokens

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5658?src=pr&el=h1) Report
> Merging [#5658](https://codecov.io/gh/huggingface/transformers/pull/5658?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2e6bb0e9c37655a03adaa3238dd6d4645fba8dc1&el=desc) will **not change** coverage.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5658/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5658?src=pr&el=tree)

```diff
@@           Coverage Diff           @@
##           master    #5658   +/-   ##
=======================================
  Coverage   78.26%   78.26%           
=======================================
  Files         145      145           
  Lines       25366    25366           
=======================================
  Hits        19852    19852           
  Misses       5514     5514           
```



------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5658?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/5658?src=pr&el=footer). Last update [2e6bb0e...8bdceb7](https://codecov.io/gh/huggingface/transformers/pull/5658?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
Create model card
Author: mrm8488
Pull request: yes
Labels: name: model card

Create model card for T5-small fine-tuned on SQUAD v2

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5655?src=pr&el=h1) Report
> Merging [#5655](https://codecov.io/gh/huggingface/transformers/pull/5655?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/2e6bb0e9c37655a03adaa3238dd6d4645fba8dc1&el=desc) will **decrease** coverage by `0.46%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5655/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5655?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5655      +/-   ##
==========================================
- Coverage   78.26%   77.80%   -0.47%     
==========================================
  Files         145      145              
  Lines       25366    25366              
==========================================
- Hits        19852    19735     -117     
- Misses       5514     5631     +117     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5655?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5655/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9vcGVuYWkucHk=) | `20.27% <0.00%> (-74.92%)` | :arrow_down: |
| [src/transformers/modeling\_openai.py](https://codecov.io/gh/huggingface/transformers/pull/5655/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19vcGVuYWkucHk=) | `79.72% <0.00%> (-1.38%)` | :arrow_down: |
| [src/transformers/file\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5655/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `79.59% <0.00%> (+0.33%)` | :arrow_up: |
| [src/transformers/generation\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5655/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `86.21% <0.00%> (+0.50%)` | :arrow_up: |
| [src/transformers/modeling\_tf\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/5655/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `95.32% <0.00%> (+31.77%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5655?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/5655?src=pr&el=footer). Last update [2e6bb0e...98c16fd](https://codecov.io/gh/huggingface/transformers/pull/5655?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
Create README.md
Author: mrm8488
Pull request: yes
Labels: name: model card

Create model card for T5-small fine-tuned on SQUAD v1.1

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5638?src=pr&el=h1) Report
> Merging [#5638](https://codecov.io/gh/huggingface/transformers/pull/5638?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/b25f7802de2749a5f8c3430437eceabf9e6384b8&el=desc) will **increase** coverage by `0.23%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5638/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5638?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5638      +/-   ##
==========================================
+ Coverage   77.52%   77.75%   +0.23%     
==========================================
  Files         145      145              
  Lines       25364    25364              
==========================================
+ Hits        19663    19723      +60     
+ Misses       5701     5641      -60     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5638?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_tf\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5638/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9yb2JlcnRhLnB5) | `43.98% <0.00%> (-49.38%)` | :arrow_down: |
| [src/transformers/generation\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5638/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `83.70% <0.00%> (-2.26%)` | :arrow_down: |
| [src/transformers/file\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5638/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9maWxlX3V0aWxzLnB5) | `79.59% <0.00%> (+0.33%)` | :arrow_up: |
| [src/transformers/modeling\_tf\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5638/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `95.53% <0.00%> (+69.51%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5638?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/5638?src=pr&el=footer). Last update [b25f780...689146c](https://codecov.io/gh/huggingface/transformers/pull/5638?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
Create README.md
Author: mrm8488
Pull request: yes
Labels: name: model card


Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/5572?src=pr&el=h1) Report
> Merging [#5572](https://codecov.io/gh/huggingface/transformers/pull/5572?src=pr&el=desc) into [master](https://codecov.io/gh/huggingface/transformers/commit/d2a93991158f15993eba9ab421d82766b892f948&el=desc) will **increase** coverage by `0.23%`.
> The diff coverage is `n/a`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/5572/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/5572?src=pr&el=tree)

```diff
@@            Coverage Diff             @@
##           master    #5572      +/-   ##
==========================================
+ Coverage   76.84%   77.07%   +0.23%     
==========================================
  Files         141      141              
  Lines       24685    24685              
==========================================
+ Hits        18969    19027      +58     
+ Misses       5716     5658      -58     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/5572?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/tokenization\_xlm\_roberta.py](https://codecov.io/gh/huggingface/transformers/pull/5572/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy90b2tlbml6YXRpb25feGxtX3JvYmVydGEucHk=) | `61.90% <0.00%> (-33.34%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_gpt2.py](https://codecov.io/gh/huggingface/transformers/pull/5572/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9ncHQyLnB5) | `65.69% <0.00%> (-29.45%)` | :arrow_down: |
| [src/transformers/generation\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/5572/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9nZW5lcmF0aW9uX3RmX3V0aWxzLnB5) | `84.96% <0.00%> (-0.26%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_electra.py](https://codecov.io/gh/huggingface/transformers/pull/5572/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl9lbGVjdHJhLnB5) | `95.38% <0.00%> (+68.46%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/5572?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/5572?src=pr&el=footer). Last update [d2a9399...e5c8277](https://codecov.io/gh/huggingface/transformers/pull/5572?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments).
Can't use AutoModelForCausalLM with bert
Author: sshearing
Pull request: no

# 🐛 Bug

## Information

Model I am using (Bert, XLNet ...): bert-base-uncased

Language I am using the model on (English, Chinese ...): English

The problem arises when using:
* [ ] my own modified scripts: (give details below)
Here is a simple 3 lines of code you can try to replicate the bug:
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained('bert-base-uncased')
model = AutoModelForCausalLM.from_pretrained('bert-base-uncased', is_decoder=True)

The tasks I am working on is:
XSUM / CNNDM summarization

## To reproduce

Steps to reproduce the behavior:

1. run the first 2 lines of code I put in the script section
2. run the first and third line of code I put in the script section

<!-- 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.-->

If you run the second line of code, you get:
AssertionError: If you want to use `BertLMHeadModel` as a standalone, add `is_decoder=True`.

If you run the third line of code (add is_decoder=True), you get:
TypeError: __init__() got an unexpected keyword argument 'is_decoder'

The first error occurs because it creates a default bert-base-uncased config, which does not set is_decoder to True. This is reasonable behavior. 

The second error occurs because when you pass in is_decoder=True, it correctly gets added to the config, but is incorrectly passed to the model __init__. In this case, BertLMHeadModel's init ONLY takes a config - it does not accept ANY kwargs. Thus we crash. I don't think this is intended behavior - I feel like its reasonable to think you can pass in is_decoder to the config you want to create in AutoModelForCausalLM without crashing.

## Expected behavior

I expect if I run the code AutoModelForCausalLM('bert-base-uncased'), I will get back a BertLMHeadModel back with the is_decoder flag set to true in the config. Alternatively, I expect if I run the code AutoModelForCausalLM('bert-base-uncased', is_decoder=True) to get the same result.

## 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: 3.0.0
- Platform: Linux-3.10.0-862.14.4.el7.x86_64-x86_64-with-centos-7.5.1804-Core
- Python version: 3.7.3
- PyTorch version (GPU?): 1.4.0 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: tried with both
- Using distributed or parallel set-up in script?: no


Comments:
Can reproduce :-) Opened a PR to fix it - thanks for the issue @sshearing !
SquadDataset should use version number in cache file name
Author: lazovich
Pull request: no

# 🐛 Bug

## Information

Model I am using (Bert, XLNet ...): N/A

Language I am using the model on (English, Chinese ...): English

The problem arises when using:
* [ ] the official example scripts:
* [x] my own modified scripts: simple example code given below

The tasks I am working on is:
* [x] an official GLUE/SQUaD task: (give the name)
* [ ] my own task or dataset: (give details below)

## To reproduce

1. Load `SquadDataset` with `args.version_2_with_negative = False`. You will see the progress bars for creating cached features.

2. Load `SquadDataset` with `args.version_2_with_negative = True`. Rather than seeing it create a new cache for the v2 dataset, you will see it automatically use the already made cache file for v1.

Example code:

```
from transformers import AutoTokenizer
from transformers import SquadDataset
from transformers import SquadDataTrainingArguments

tokenizer = AutoTokenizer.from_pretrained('bert-base-uncased')
args = SquadDataTrainingArguments()

# FIXME: Change this path to your local SQuAD dataset path
args.data_dir = os.path.expanduser("~/.torch/nlp/SQuAD")

args.version_2_with_negative = False
squadv1 = SquadDataset(args, tokenizer)

args.version_2_with_negative = True
squadv2 = SquadDataset(args, tokenizer)
```
## Expected behavior

Separate cache files should be created for the v1.1 and v2 versions of SQuAD

## Environment info

- `transformers` version: 3.0.2
- Platform: Linux-5.0.0-1035-azure-x86_64-with-Ubuntu-18.04-bionic
- Python version: 3.7.7
- PyTorch version (GPU?): 1.5.0 (True)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: N/A
- Using distributed or parallel set-up in script?: no


Comments:
closes by your own #5669 Thanks for your contribution :)
tokenizer.batch_encoder_plus do not return input_len
Author: max-yue
Pull request: no
Labels: name: wontfix

# 🚀 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,
                pad_to_max_length=True,
            )
            for ex_id, (input_ids, segment_ids, input_mask) in enumerate(zip(batch_tokens["input_ids"],
                                                                             batch_tokens["token_type_ids"],
                                                                             batch_tokens["attention_mask"])):
                input_len = sum(1 for id in input_ids if id != self.tokenizer.pad_token_id)
```

if return input_len, it will be great.

## Motivation

<!-- Please outline the motivation for the proposal. Is your feature request
     related to a problem? e.g., I'm always frustrated when [...]. If this is related
     to another GitHub issue, please link here too. -->

## Your contribution

<!-- Is there any way that you could help, e.g. by submitting a PR?
     Make sure to read the CONTRIBUTING.MD readme:
     https://github.com/huggingface/transformers/blob/master/CONTRIBUTING.md -->


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.
Fix Albert Attention
Author: ZhuBaohe
Pull request: yes
Labels: name: wontfix

This PR simplifies  the code of class AlbertAttention.

Comments:
# [Codecov](https://codecov.io/gh/huggingface/transformers/pull/4188?src=pr&el=h1) Report
> 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** coverage by `0.00%`.
> The diff coverage is `100.00%`.

[![Impacted file tree graph](https://codecov.io/gh/huggingface/transformers/pull/4188/graphs/tree.svg?width=650&height=150&src=pr&token=9qOlN6Hb1c)](https://codecov.io/gh/huggingface/transformers/pull/4188?src=pr&el=tree)

```diff
@@           Coverage Diff           @@
##           master    #4188   +/-   ##
=======================================
  Coverage   78.10%   78.11%           
=======================================
  Files         117      117           
  Lines       18962    18963    +1     
=======================================
+ Hits        14811    14813    +2     
+ Misses       4151     4150    -1     
```


| [Impacted Files](https://codecov.io/gh/huggingface/transformers/pull/4188?src=pr&el=tree) | Coverage Δ | |
|---|---|---|
| [src/transformers/modeling\_albert.py](https://codecov.io/gh/huggingface/transformers/pull/4188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ19hbGJlcnQucHk=) | `75.38% <100.00%> (+0.06%)` | :arrow_up: |
| [src/transformers/modeling\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ191dGlscy5weQ==) | `90.92% <0.00%> (-0.13%)` | :arrow_down: |
| [src/transformers/modeling\_tf\_utils.py](https://codecov.io/gh/huggingface/transformers/pull/4188/diff?src=pr&el=tree#diff-c3JjL3RyYW5zZm9ybWVycy9tb2RlbGluZ190Zl91dGlscy5weQ==) | `92.93% <0.00%> (+0.32%)` | :arrow_up: |

------

[Continue to review full report at Codecov](https://codecov.io/gh/huggingface/transformers/pull/4188?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/4188?src=pr&el=footer). Last update [877fc56...7c64f23](https://codecov.io/gh/huggingface/transformers/pull/4188?src=pr&el=lastupdated). Read the [comment docs](https://docs.codecov.io/docs/pull-request-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.
New run_language_modeling.py does not save vocab.txt and tokenizer_config.json
Author: questpavan
Pull request: no

# 🐛 Bug
Hi, 

While running new  run_language_modeling.py, at the end it only saves pytorch model and config.json and training arguments
Unlike before it also used to store vocab.txt and tokenizer_config.json

 I am not using any custom tokenizer, only using tokenizer provided by the model.

## Command Details I used

python run_language_modeling.py 
--output_dir=bert-base-uncased-4 
--overwrite_output_dir 
--model_type=bert 
--model_name_or_path="bert-base-uncased" 
--do_train --train_data_file="./test.txt" 
--per_gpu_train_batch_size 3 
--mlm 
--num_train_epochs 1

Model I am using (Bert, XLNet ...):
Bert-base-uncased 

Language I am using the model on (English, Chinese ...):
Engilsh


## Expected behavior
It should also save vocab.txt and tokenizer_config.json



Comments:
Yes, you would now need to do it manually by calling `tokenizer.save_pretrained(training_args.output_dir)`

I'll keep this issue open to see if many people ask for it (we can re-add if it's the case). cc @LysandreJik 

I think if an extra step is needed, it should say it in the guideline ;) 
So perhaps auto save would be better.

Ok, I will re-add it by default
What is the decoder_input for encoder-decoder transformer in training time?
Author: guotong1988
Pull request: no

https://datascience.stackexchange.com/questions/76261/whats-the-input-dimension-for-transformer-decoder-during-training

Is the link's answer right?

Thank you very much!

Comments:
The spirit of the answer is right. There is a lot more detail in this [blogpost](https://sshleifer.github.io/blog_v2/jupyter/2020/03/12/bart.html)

In the future, this would be a great Q for our forums: https://discuss.huggingface.co/ since it doesn't directly involve issues with the library. 

Thank you again.