GitLab

* added resources: links to task guides that support these models

* minor polishing

* conflict resolved

* link fix

* Update docs/source/en/model_doc/vision-encoder-decoder.mdx
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add resources

* Add more resources

* Add more resources

* Add TAPAS

* Fix pipeline tag

* Fix pipeline tags

* Remove pipeline tag

* Remove depth-estimation tag

* Update docs/source/en/model_doc/segformer.mdx
Co-authored-by: Maria Khalusova <kafooster@gmail.com>

* Apply suggestion

* Fix segformer
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
Co-authored-by: Maria Khalusova <kafooster@gmail.com>

* Update doc example feature extractor -> image processor

* Apply suggestions from code review

* add model files etc for MobileNetV2

* rename files for MobileNetV1

* initial implementation of MobileNetV1

* fix conversion script

* cleanup

* write docs

* tweaks

* fix conversion script

* extract hidden states

* fix test cases

* make fixup

* fixup it all

* rename V1 to V2

* fix checkpoints

* fixup

* implement first block + weight conversion

* add remaining layers

* add output stride and dilation

* fixup

* add tests

* add deeplabv3+ head

* a bit of fixup

* finish deeplab conversion

* add link to doc

* fix issue with JIT trace

in_height and in_width would be Tensor objects during JIT trace, which caused Core ML conversion to fail on the remainder op. By making them ints, the result of the padding calculation becomes a constant value.

* cleanup

* fix order of models

* fix rebase error

* remove main from doc link

* add image processor

* remove old feature extractor

* fix converter + other issues

* fixup

* fix unit test

* add to onnx tests (but these appear broken now)

* add post_process_semantic_segmentation

* use google org

* remove unused imports

* move args

* replace weird assert