Adding task guides to resources (#21704)

* 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>

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

docs/source/en/model_doc/plbart.mdx

@@ -78,6 +78,13 @@ it's passed with the `text_target` keyword argument.
 "Returns the maximum value of a b c."
 ```
 
+## Documentation resources
+
+- [Text classification task guide](./tasks/sequence_classification)
+- [Causal language modeling task guide](./tasks/language_modeling)
+- [Translation task guide](./tasks/translation)
+- [Summarization task guide](./tasks/summarization)
+
 ## PLBartConfig
 
 [[autodoc]] PLBartConfig

docs/source/en/model_doc/poolformer.mdx

@@ -48,6 +48,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 <PipelineTag pipeline="image-classification"/>
 
 - [`PoolFormerForImageClassification`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/image-classification) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb).
+- See also: [Image classification task guide](./tasks/image_classification)
 
 If you're interested in submitting a resource to be included here, please feel free to open a Pull Request and we'll review it! The resource should ideally demonstrate something new instead of duplicating an existing resource.
 

docs/source/en/model_doc/prophetnet.mdx

@@ -53,6 +53,11 @@ Tips:
 
 The Authors' code can be found [here](https://github.com/microsoft/ProphetNet).
 
+## Documentation resources
+
+- [Causal language modeling task guide](./tasks/language_modeling)
+- [Translation task guide](./tasks/translation)
+- [Summarization task guide](./tasks/summarization)
 
 ## ProphetNetConfig
 

docs/source/en/model_doc/qdqbert.mdx

@@ -114,6 +114,15 @@ the instructions in [torch.onnx](https://pytorch.org/docs/stable/onnx.html). Exa
 >>> torch.onnx.export(...)
 ```
 
+## Documentation resources
+
+- [Text classification task guide](./tasks/sequence_classification)
+- [Token classification task guide](./tasks/token_classification)
+- [Question answering task guide](./tasks/question_answering)
+- [Causal language modeling task guide](./tasks/language_modeling)
+- [Masked language modeling task guide](./tasks/masked_language_modeling)
+- [Multiple choice task guide](./tasks/multiple_choice)
+
 ## QDQBertConfig
 
 [[autodoc]] QDQBertConfig

docs/source/en/model_doc/reformer.mdx

@@ -151,6 +151,13 @@ input_ids = tokenizer.encode("This is a sentence from the training data", return
 loss = model(input_ids, labels=input_ids)[0]
 ```
 
+## Documentation resources
+
+- [Text classification task guide](./tasks/sequence_classification)
+- [Question answering task guide](./tasks/question_answering)
+- [Causal language modeling task guide](./tasks/language_modeling)
+- [Masked language modeling task guide](./tasks/masked_language_modeling)
+
 ## ReformerConfig
 
 [[autodoc]] ReformerConfig

docs/source/en/model_doc/regnet.mdx

@@ -38,6 +38,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 <PipelineTag pipeline="image-classification"/>
 
 - [`RegNetForImageClassification`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/image-classification) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb).
+- See also: [Image classification task guide](./tasks/image_classification)
 
 If you're interested in submitting a resource to be included here, please feel free to open a Pull Request and we'll review it! The resource should ideally demonstrate something new instead of duplicating an existing resource.
 

docs/source/en/model_doc/rembert.mdx

@@ -37,6 +37,15 @@ embedding layer. The embeddings are not tied in pre-training, in contrast with B
 embeddings (preserved during fine-tuning) and bigger output embeddings (discarded at fine-tuning). The tokenizer is
 also similar to the Albert one rather than the BERT one.
 
+## Documentation resources
+
+- [Text classification task guide](./tasks/sequence_classification)
+- [Token classification task guide](./tasks/token_classification)
+- [Question answering task guide](./tasks/question_answering)
+- [Causal language modeling task guide](./tasks/language_modeling)
+- [Masked language modeling task guide](./tasks/masked_language_modeling)
+- [Multiple choice task guide](./tasks/multiple_choice)
+
 ## RemBertConfig
 
 [[autodoc]] RemBertConfig

docs/source/en/model_doc/resnet.mdx

@@ -40,6 +40,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 <PipelineTag pipeline="image-classification"/>
 
 - [`ResNetForImageClassification`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/image-classification) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb).
+- See also: [Image classification task guide](./tasks/image_classification)
 
 If you're interested in submitting a resource to be included here, please feel free to open a Pull Request and we'll review it! The resource should ideally demonstrate something new instead of duplicating an existing resource.
 

docs/source/en/model_doc/roberta-prelayernorm.mdx

@@ -29,6 +29,14 @@ Tips:
 This model was contributed by [andreasmaden](https://huggingface.co/andreasmaden).
 The original code can be found [here](https://github.com/princeton-nlp/DinkyTrain).
 
+## Documentation resources
+
+- [Text classification task guide](./tasks/sequence_classification)
+- [Token classification task guide](./tasks/token_classification)
+- [Question answering task guide](./tasks/question_answering)
+- [Causal language modeling task guide](./tasks/language_modeling)
+- [Masked language modeling task guide](./tasks/masked_language_modeling)
+- [Multiple choice task guide](./tasks/multiple_choice)
 
 ## RobertaPreLayerNormConfig
 

docs/source/en/model_doc/roberta.mdx

@@ -70,6 +70,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 - [`RobertaForSequenceClassification`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/text-classification) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification.ipynb).
 - [`TFRobertaForSequenceClassification`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/tensorflow/text-classification) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification-tf.ipynb).
 - [`FlaxRobertaForSequenceClassification`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/flax/text-classification) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/text_classification_flax.ipynb).
+- [Text classification task guide](./tasks/sequence_classification)
 
 <PipelineTag pipeline="token-classification"/>
 
@@ -77,6 +78,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 - [`TFRobertaForTokenClassification`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/tensorflow/token-classification) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/token_classification-tf.ipynb).
 - [`FlaxRobertaForTokenClassification`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/flax/token-classification).
 - [Token classification](https://huggingface.co/course/chapter7/2?fw=pt) chapter of the 🤗 Hugging Face Course.
+- [Token classification task guide](./tasks/token_classification)
 
 <PipelineTag pipeline="fill-mask"/>
 
@@ -85,6 +87,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 - [`TFRobertaForMaskedLM`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/tensorflow/language-modeling#run_mlmpy) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/language_modeling-tf.ipynb).
 - [`FlaxRobertaForMaskedLM`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/flax/language-modeling#masked-language-modeling) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/masked_language_modeling_flax.ipynb).
 - [Masked language modeling](https://huggingface.co/course/chapter7/3?fw=pt) chapter of the 🤗 Hugging Face Course.
+- [Masked language modeling task guide](./tasks/masked_language_modeling)
 
 <PipelineTag pipeline="question-answering"/>
 
@@ -93,10 +96,12 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 - [`TFRobertaForQuestionAnswering`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/tensorflow/question-answering) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/question_answering-tf.ipynb).
 - [`FlaxRobertaForQuestionAnswering`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/flax/question-answering).
 - [Question answering](https://huggingface.co/course/chapter7/7?fw=pt) chapter of the 🤗 Hugging Face Course.
+- [Question answering task guide](./tasks/question_answering)
 
 **Multiple choice**
 - [`RobertaForMultipleChoice`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/multiple-choice) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/multiple_choice.ipynb).
 - [`TFRobertaForMultipleChoice`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/tensorflow/multiple-choice) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/multiple_choice-tf.ipynb).
+- [Multiple choice task guide](./tasks/multiple_choice)
 
 ## RobertaConfig
 

docs/source/en/model_doc/roc_bert.mdx

@@ -31,6 +31,15 @@ in the toxic content detection task under human-made attacks.*
 
 This model was contributed by [weiweishi](https://huggingface.co/weiweishi).
 
+## Documentation resources
+
+- [Text classification task guide](./tasks/sequence_classification)
+- [Token classification task guide](./tasks/token_classification)
+- [Question answering task guide](./tasks/question_answering)
+- [Causal language modeling task guide](./tasks/language_modeling)
+- [Masked language modeling task guide](./tasks/masked_language_modeling)
+- [Multiple choice task guide](./tasks/multiple_choice)
+
 ## RoCBertConfig
 
 [[autodoc]] RoCBertConfig

docs/source/en/model_doc/roformer.mdx

@@ -37,6 +37,15 @@ Tips:
 
 This model was contributed by [junnyu](https://huggingface.co/junnyu). The original code can be found [here](https://github.com/ZhuiyiTechnology/roformer).
 
+## Documentation resources
+
+- [Text classification task guide](./tasks/sequence_classification)
+- [Token classification task guide](./tasks/token_classification)
+- [Question answering task guide](./tasks/question_answering)
+- [Causal language modeling task guide](./tasks/language_modeling)
+- [Masked language modeling task guide](./tasks/masked_language_modeling)
+- [Multiple choice task guide](./tasks/multiple_choice)
+
 ## RoFormerConfig
 
 [[autodoc]] RoFormerConfig

docs/source/en/model_doc/segformer.mdx

@@ -91,6 +91,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 <PipelineTag pipeline="image-classification"/>
 
 - [`SegformerForImageClassification`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/image-classification) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb).
+- [Image classification task guide](./tasks/image_classification)
 
 Semantic segmentation:
 
@@ -98,6 +99,7 @@ Semantic segmentation:
 - A blog on fine-tuning SegFormer on a custom dataset can be found [here](https://huggingface.co/blog/fine-tune-segformer).
 - More demo notebooks on SegFormer (both inference + fine-tuning on a custom dataset) can be found [here](https://github.com/NielsRogge/Transformers-Tutorials/tree/master/SegFormer).
 - [`TFSegformerForSemanticSegmentation`] is supported by this [example notebook](https://github.com/huggingface/notebooks/blob/main/examples/semantic_segmentation-tf.ipynb).
+- [Semantic segmentation task guide](./tasks/semantic_segmentation)
 
 If you're interested in submitting a resource to be included here, please feel free to open a Pull Request and we'll review it! The resource should ideally demonstrate something new instead of duplicating an existing resource.
 

docs/source/en/model_doc/sew-d.mdx

@@ -36,6 +36,10 @@ Tips:
 
 This model was contributed by [anton-l](https://huggingface.co/anton-l).
 
+## Documentation resources
+
+- [Audio classification task guide](./tasks/audio_classification)
+- [Automatic speech recognition task guide](./tasks/asr)
 
 ## SEWDConfig
 

docs/source/en/model_doc/sew.mdx

@@ -36,6 +36,10 @@ Tips:
 
 This model was contributed by [anton-l](https://huggingface.co/anton-l).
 
+## Documentation resources
+
+- [Audio classification task guide](./tasks/audio_classification)
+- [Automatic speech recognition task guide](./tasks/asr)
 
 ## SEWConfig
 

docs/source/en/model_doc/speech_to_text_2.mdx

@@ -94,6 +94,9 @@ predicted token ids.
 
 See [model hub](https://huggingface.co/models?filter=speech2text2) to look for Speech2Text2 checkpoints.
 
+## Documentation resources
+
+- [Causal language modeling task guide](./tasks/language_modeling)
 
 ## Speech2Text2Config
 

docs/source/en/model_doc/splinter.mdx

@@ -47,6 +47,10 @@ Tips:
 
 This model was contributed by [yuvalkirstain](https://huggingface.co/yuvalkirstain) and [oriram](https://huggingface.co/oriram). The original code can be found [here](https://github.com/oriram/splinter).
 
+## Documentation resources
+
+- [Question answering task guide](./tasks/question-answering)
+
 ## SplinterConfig
 
 [[autodoc]] SplinterConfig

docs/source/en/model_doc/squeezebert.mdx

@@ -46,6 +46,13 @@ Tips:
 
 This model was contributed by [forresti](https://huggingface.co/forresti).
 
+## Documentation resources
+
+- [Text classification task guide](./tasks/sequence_classification)
+- [Token classification task guide](./tasks/token_classification)
+- [Question answering task guide](./tasks/question_answering)
+- [Masked language modeling task guide](./tasks/masked_language_modeling)
+- [Multiple choice task guide](./tasks/multiple_choice)
 
 ## SqueezeBertConfig
 

docs/source/en/model_doc/swin.mdx

@@ -52,6 +52,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 <PipelineTag pipeline="image-classification"/>
 
 - [`SwinForImageClassification`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/image-classification) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb).
+- See also: [Image classification task guide](./tasks/image_classification)
 
 Besides that:
 

docs/source/en/model_doc/swinv2.mdx

@@ -33,6 +33,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 <PipelineTag pipeline="image-classification"/>
 
 - [`Swinv2ForImageClassification`] is supported by this [example script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/image-classification) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/image_classification.ipynb).
+- See also: [Image classification task guide](./tasks/image_classification)
 
 Besides that: