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But does it really work?

* Implement object-detection pipeline

* Define threshold const

* Add `threshold` argument

* Refactor

* Uncomment test inputs

* `rm
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix typo
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* Fix typo
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* Chore better doc
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* Rm unnecessary lines
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Chore better naming
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* Update src/transformers/pipelines/object_detection.py
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* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix typo

* Add `detr-tiny` for tests

* Add `ObjectDetectionPipeline` to `trnsfrmrs/init`

* Implement new bbox format

* Update detr post_process

* Update `load_img` method obj det pipeline

* make style

* Implement new testing format for obj det pipeln

* Add guard pytorch specific code in pipeline

* Add doc

* Make pipeline_obj_tet tests deterministic

* Revert some changes to `post_process` COCO api

* Chore

* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/pipelines/object_detection.py
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* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/pipelines/object_detection.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Rm timm requirement

* make fixup

* Add timm requirement to test

* Make fixup

* Guard torch.Tensor

* Chore

* Delete unnecessary comment
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix Tensorflow T5 with int64 input

* Style pass

* Better error raised when cloned without lfs

* add from e

* Complete basic mechanism

* Save

* Complete everything

* Style & Quality

* Update READMEs

* Add testing

* Fix README.md format

* Apply suggestions

* Fix format

* Update utils/check_copies.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix logit_scale init

* add logit_scale_init_value as config param

* Deprecated Mirror

* revert

* revert

* revert

* fix

* [docs] update dead quickstart link on resuing past for GPT2

Thed dead link have been replaced by two links of forward and call methods of the GPT2 class for torch and tensorflow respectively.

* [docs] fix formatting for gpt2 page update

* Optimized bad word ids generation

* Fixed optimized bad token ids

* Updated style

* ✅ Update image-classification example's tests

* 🔥 remove cats_and_dogs test samples

* 💄 fix flake8

* Add conversion of TapasForMaskedLM

* Add copied from statements

* refactor GPT Config to allow dyn. properties

* make attribute_map a class attribute

* remove old code

* update unit test to test config: Add test for common properties setter

* update unit test to test config: Add test for common properties passed as parameters to __init__

* update to black code format

* Allow that setters are not defined for certain config classes

* update config classes to implement attribute_map

* bugfix lxmert config - id2labels was not defined when num_labels was set

* update broken configs - add attribute_maps

* update bart config

* update black codestyle

* update documentation on common config attributes

* update GPTJ config to new attribute map

* update docs on common attributes

* gptj config: add max_position_embeddings

* gptj config: format with black

* update speech to text 2 config

* format doc file to max_len 119

* update config template

* Adding a test for multibytes unicode.

* Adding some accents.

* Making sure decoding works.

* Make tests passing by being cheesy.

* Add inputs to pretrained tests

* Make style

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* ✨ add pytorch image classification example

* 🔥 remove utils.py

* 💄 fix flake8 style issues

* 🔥 remove unnecessary line

* ✨ limit dataset sizes

* 📌 update reqs

* 🎨 restructure - use datasets lib

* 🎨 import transforms directly

* 📝 add comments

* 💄 style

* 🔥 remove flag

* 📌 update requirement warning

* 📝 add vision README.md

* 📝 update README.md

* 📝 update README.md

* 🎨 add image-classification tag to model card

* 🚚 rename vision ➡️ image-classification

* 📝 update image-classification README.md

* [docs] Update perplexity.rst to use negative log likelihood

Model `forward` returns the negative log likelihood. The document correctly defines and calculates perplexity, but the description and variable names are inconsistent, which might cause confusion.

* [docs] restyle perplexity.rst

* correct order of overflowing_tokens for slow tokenizer (issue fix #13148)

* python 3.9 requires sentencepiece version 0.1.94 or above

* slicing of ids fixed in truncated_sequence()

* Update setup.py

* Correct order of overflowing tokens for pair of sentences

* code reformatted

* Update tokenization_utils_base.py

* reformatting file

* test to check single_input added

* missing function restored

* test to check pair_input overflowing tokens order

* test to check pair_input overflowing tokens order

* test to check pair_input overflowing tokens order

* added an error message for pair of seq and longest_first strategy

* test for pair_input modified

* variable name corrected

* fixed a typo in error message

* requested changes implemented

* required test added

* Corrected the message to match test message

* added error message for Luke Tokenizer

* lost test recovered

* docstring for truncate_sequences and prepare_for_model updated

* docstring for luke tokenizer updated

* updated ENCODE_PLUS_ADDITIONAL_KWARGS_DOCSTRING

* aligned text and fixed puncuatations

* improved style and quality of code

* fixed error_msg in truncate_sequences

* replaced encode_plus method with regular call method

* clean up

* rephrased the docstring

`audio-classification`.

* Update clip loss calculation

Hello, I'm the author of the blog you took the snippet from. I think this way of calculating is possibly slightly more accurate for calculation.

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

[Flax/run_hybrid_clip] Fix duplicating images when captions_per_image exceeds the number of captions, enable truncation 

* finish

* finish