GitLab

* Add pip install update to resolve import error

Add pip install upgrade tensorflow-gpu to remove error below:
```
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-2-094fadb93f3f> in <module>()
      1 import torch
----> 2 from transformers import AutoModel, AutoTokenizer, BertTokenizer
      3 
      4 torch.set_grad_enabled(False)

4 frames
/usr/local/lib/python3.6/dist-packages/transformers/__init__.py in <module>()
    133 
    134 # Pipelines
--> 135 from .pipelines import (
    136     Conversation,
    137     ConversationalPipeline,

/usr/local/lib/python3.6/dist-packages/transformers/pipelines.py in <module>()
     46     import tensorflow as tf
     47 
---> 48     from .modeling_tf_auto import (
     49         TF_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
     50         TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,

/usr/local/lib/python3.6/dist-packages/transformers/modeling_tf_auto.py in <module>()
     49 from .configuration_utils import PretrainedConfig
     50 from .file_utils import add_start_docstrings
---> 51 from .modeling_tf_albert import (
     52     TFAlbertForMaskedLM,
     53     TFAlbertForMultipleChoice,

/usr/local/lib/python3.6/dist-packages/transformers/modeling_tf_albert.py in <module>()
     22 import tensorflow as tf
     23 
---> 24 from .activations_tf import get_tf_activation
     25 from .configuration_albert import AlbertConfig
     26 from .file_utils import (

/usr/local/lib/python3.6/dist-packages/transformers/activations_tf.py in <module>()
     52     "gelu": tf.keras.layers.Activation(gelu),
     53     "relu": tf.keras.activations.relu,
---> 54     "swish": tf.keras.activations.swish,
     55     "silu": tf.keras.activations.swish,
     56     "gelu_new": tf.keras.layers.Activation(gelu_new),

AttributeError: module 'tensorflow_core.python.keras.api._v2.keras.activations' has no attribute 'swish'
```
I have tried running the colab after this change and it seems to work fine (all the cells run with no errors).

* Update notebooks/02-transformers.ipynb

only need to upgrade tensorflow, not tensorflow-gpu.
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* create README.md

* Apply suggestions from code review
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Create README.md

* correct metrics id

cc @lhoestq
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* refactored exisiting nested loops to vectorized implementation

* replaced explicit indexing with torch.where

* modifying score for previous input_ids only

* replace init_ddp_connection for index init

* style

* add finetune test

* add test data

* move generate tensors to device

* add test on EM metric

* style

* allow multi process test

* keep gloo process group for retrieval

* add multi-gpu test

* use custom accelerator

* clean test finetune

* minor

* style

* style

* typo

* use python call instead of imported main fumction

* return_dict fix in modeling_rag

* use float32 in retrieval

* store as float32 as well in the custom knowledge dataset example

* style

* rename to finetune_rag

* style

* update readme

* rename utils and callbacks to utils_rag and callbacks_rag

* fix test

* patrick's comments

* generate dummy data in the finetue test script

* remove dummy data files

* style

* Update the bibtex with EMNLP demo

* Update README.md

* Update README.md

* Fix the CI and tests

* Fix quality

* Remove that m form nowhere

* fix deprecation warning

* fix

The heading was originally uncased, which did not reflect the contents of this README. Changed it to cased.

You may be unaware but you're running some software that meddles with every commit on https://github.com/huggingface/transformers/

Something is wrong with the software you're using. It adds a reference to almost every PR in the master tree. Which is very wrong. Please check your software and please don't do it again.

Example:
see the bottom of this PR and most other PRs:
https://github.com/huggingface/transformers/pull/8639

* don't reconvert when the type is already right

* better name

* adjust logic as suggested

* merge

* Fix run_ner script

* Pin datasets

* `disable_ngram_loss` fix for prophetnet

* add changes documentation

* fix _compute_loss to use mean reduction and -100 to masked tokens & remove unnecessary arguments

* mean label smoothing loss

* small refactor

* fix test
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

Fixed a small typo on the XLNet and permutation language modelling section

* Better filtering of the model outputs in Trainer

* Fix examples tests

* Add test for Lysandre

* CI should install `sentencepiece`

* Requiring TF

* Fixing some TFDPR bugs

* remove return_dict=False/True hack
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

* working on LongformerForSequenceClassification

* add TFLongformerForMultipleChoice

* add TFLongformerForTokenClassification

* use add_start_docstrings_to_model_forward

* test TFLongformerForSequenceClassification

* test TFLongformerForMultipleChoice

* test TFLongformerForTokenClassification

* remove test from repo

* add test and doc for TFLongformerForSequenceClassification, TFLongformerForTokenClassification, TFLongformerForMultipleChoice

* add requested classes to modeling_tf_auto.py
update dummy_tf_objects
fix tests
fix bugs in requested classes

* pass all tests except test_inputs_embeds

* sync with master

* pass all tests except test_inputs_embeds

* pass all tests

* pass all tests

* work on test_inputs_embeds

* fix style and quality

* make multi choice work

* fix TFLongformerForTokenClassification signature

* fix TFLongformerForMultipleChoice, TFLongformerForSequenceClassification signature

* fix mult choice

* fix mc hint

* fix input embeds

* fix input embeds

* refactor input embeds

* fix copy issue

* apply sylvains changes and clean more
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

the table was badly formatted because of a single line break

* docs(bert-base-15lang-cased): add model card

* add cards for all Geotrend models

* [model cards] fix language tag for all Geotrend models

* Updated the Extractive Question Answering code snippets

The Extractive Question Answering code snippets do not work anymore since the models return task-specific output objects. This commit fixes the pytorch and tensorflow examples but adding `.values()` to the model call.

* Update task_summary.rst

* apex breaks return_dict obj

* style

* Updated ModelCard

* Apply suggestions from code review
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Model card: T5-base fine-tuned on QuaRTz

* Update model_cards/mrm8488/t5-base-finetuned-quartz/README.md
Co-authored-by: Julien Chaumond <chaumond@gmail.com>