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/markuplm.mdx

@@ -193,6 +193,12 @@ all nodes and xpaths yourself, you can provide them directly to the processor. M
 dict_keys(['input_ids', 'token_type_ids', 'attention_mask', 'xpath_tags_seq', 'xpath_subs_seq'])
 ```
 
+## Documentation resources
+
+- [Text classification task guide](./tasks/sequence_classification)
+- [Token classification task guide](./tasks/token_classification)
+- [Question answering task guide](./tasks/question_answering)
+
 ## MarkupLMConfig
 
 [[autodoc]] MarkupLMConfig

docs/source/en/model_doc/mbart.mdx

@@ -152,6 +152,15 @@ tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)
 # => "The Secretary-General of the United Nations says there is no military solution in Syria."
 ```
 
+## 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)
+- [Translation task guide](./tasks/translation)
+- [Summarization task guide](./tasks/summarization)
+
 ## MBartConfig
 
 [[autodoc]] MBartConfig

docs/source/en/model_doc/mctct.mdx

@@ -31,6 +31,9 @@ performance for many languages that also transfers well to LibriSpeech.*
 
 This model was contributed by [cwkeam](https://huggingface.co/cwkeam). The original code can be found [here](https://github.com/flashlight/wav2letter/tree/main/recipes/mling_pl).
 
+## Documentation resources
+
+- [Automatic speech recognition task guide](./tasks/asr)
 
 Tips:
 

docs/source/en/model_doc/megatron-bert.mdx

@@ -78,6 +78,15 @@ This model was contributed by [jdemouth](https://huggingface.co/jdemouth). The o
 Megatron Language models. In particular, it contains a hybrid model parallel approach using "tensor parallel" and
 "pipeline parallel" techniques.
 
+## 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)
+
 ## MegatronBertConfig
 
 [[autodoc]] MegatronBertConfig

docs/source/en/model_doc/mobilebert.mdx

@@ -43,6 +43,14 @@ Tips:
 
 This model was contributed by [vshampor](https://huggingface.co/vshampor). The original code can be found [here](https://github.com/google-research/mobilebert).
 
+## 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)
+
 ## MobileBertConfig
 
 [[autodoc]] MobileBertConfig

docs/source/en/model_doc/mobilenet_v1.mdx

@@ -51,6 +51,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 <PipelineTag pipeline="image-classification"/>
 
 - [`MobileNetV1ForImageClassification`] 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/mobilenet_v2.mdx

@@ -55,6 +55,10 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 <PipelineTag pipeline="image-classification"/>
 
 - [`MobileNetV2ForImageClassification`] 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)
+
+**Semantic segmentation**
+- [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/mobilevit.mdx

@@ -64,6 +64,10 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 <PipelineTag pipeline="image-classification"/>
 
 - [`MobileViTForImageClassification`] 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)
+
+**Semantic segmentation**
+- [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/mpnet.mdx

@@ -40,6 +40,14 @@ Tips:
 
 The original code can be found [here](https://github.com/microsoft/MPNet).
 
+## 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)
+
 ## MPNetConfig
 
 [[autodoc]] MPNetConfig

docs/source/en/model_doc/mt5.mdx

@@ -56,6 +56,11 @@ Google has released the following variants:
 This model was contributed by [patrickvonplaten](https://huggingface.co/patrickvonplaten). The original code can be
 found [here](https://github.com/google-research/multilingual-t5).
 
+## Documentation resources
+
+- [Translation task guide](./tasks/translation)
+- [Summarization task guide](./tasks/summarization)
+
 ## MT5Config
 
 [[autodoc]] MT5Config

docs/source/en/model_doc/mvp.mdx

@@ -100,6 +100,15 @@ For lightweight tuning, *i.e.*, fixing the model and only tuning prompts, you ca
 >>> model.set_lightweight_tuning()
 ```
 
+## 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)
+- [Translation task guide](./tasks/translation)
+- [Summarization task guide](./tasks/summarization)
+
 ## MvpConfig
 
 [[autodoc]] MvpConfig

docs/source/en/model_doc/nat.mdx

@@ -63,6 +63,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 <PipelineTag pipeline="image-classification"/>
 
 - [`NatForImageClassification`] 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/nezha.mdx

@@ -31,6 +31,14 @@ and natural language inference (XNLI).*
 
 This model was contributed by [sijunhe](https://huggingface.co/sijunhe). The original code can be found [here](https://github.com/huawei-noah/Pretrained-Language-Model/tree/master/NEZHA-PyTorch).
 
+## 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)
+
 ## NezhaConfig
 
 [[autodoc]] NezhaConfig

docs/source/en/model_doc/nllb.mdx

@@ -88,6 +88,11 @@ See example below for a translation from romanian to german:
 UN-Chef sagt, es gibt keine militärische Lösung in Syrien
 ```
 
+## Documentation resources
+
+- [Translation task guide](./tasks/translation)
+- [Summarization task guide](./tasks/summarization)
+
 ## NllbTokenizer
 
 [[autodoc]] NllbTokenizer

docs/source/en/model_doc/nystromformer.mdx

@@ -33,6 +33,14 @@ favorably relative to other efficient self-attention methods. Our code is availa
 
 This model was contributed by [novice03](https://huggingface.co/novice03). The original code can be found [here](https://github.com/mlpen/Nystromformer).
 
+## 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)
+
 ## NystromformerConfig
 
 [[autodoc]] NystromformerConfig

docs/source/en/model_doc/openai-gpt.mdx

@@ -73,6 +73,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 <PipelineTag pipeline="text-classification"/>
 
 - A blog post on [outperforming OpenAI GPT-3 with SetFit for text-classification](https://www.philschmid.de/getting-started-setfit).
+- See also: [Text classification task guide](./tasks/sequence_classification)
 
 <PipelineTag pipeline="text-generation"/>
 
@@ -86,6 +87,7 @@ A list of official Hugging Face and community (indicated by 🌎) resources to h
 - [Causal language modeling](https://huggingface.co/course/en/chapter7/6?fw=pt#training-a-causal-language-model-from-scratch) chapter of the 🤗 Hugging Face Course.
 - [`OpenAIGPTLMHeadModel`] is supported by this [causal language modeling example script](https://github.com/huggingface/transformers/tree/main/examples/pytorch/language-modeling#gpt-2gpt-and-causal-language-modeling), [text generation example script](https://github.com/huggingface/transformers/blob/main/examples/pytorch/text-generation/run_generation.py) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/language_modeling.ipynb).
 - [`TFOpenAIGPTLMHeadModel`] is supported by this [causal language modeling example script](https://github.com/huggingface/transformers/tree/main/examples/tensorflow/language-modeling#run_clmpy) and [notebook](https://colab.research.google.com/github/huggingface/notebooks/blob/main/examples/language_modeling-tf.ipynb).
+- See also: [Causal language modeling task guide](./tasks/language_modeling)
 
 <PipelineTag pipeline="token-classification"/>
 

docs/source/en/model_doc/opt.mdx

@@ -45,7 +45,7 @@ The resource should ideally demonstrate something new instead of duplicating an
 
 <PipelineTag pipeline="text-classification" />
 
-- [Token classification](https://huggingface.co/course/chapter7/2?fw=pt) chapter of the 🤗 Hugging Face Course.
+- [Text classification task guide](sequence_classification.mdx)
 - [`OPTForSequenceClassification`] 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).
 
 <PipelineTag pipeline="question-answering" />
@@ -56,7 +56,7 @@ The resource should ideally demonstrate something new instead of duplicating an
 
 ⚡️ Inference
 
-- A blog bost on [How 🤗 Accelerate runs very large models thanks to PyTorch](https://huggingface.co/blog/accelerate-large-models) with OPT.
+- A blog post on [How 🤗 Accelerate runs very large models thanks to PyTorch](https://huggingface.co/blog/accelerate-large-models) with OPT.
 
 ## OPTConfig
 

docs/source/en/model_doc/pegasus.mdx

@@ -102,6 +102,12 @@ All the [checkpoints](https://huggingface.co/models?search=pegasus) are fine-tun
 ... )
 ```
 
+## Documentation resources
+
+- [Causal language modeling task guide](./tasks/language_modeling)
+- [Translation task guide](./tasks/translation)
+- [Summarization task guide](./tasks/summarization)
+
 ## PegasusConfig
 
 [[autodoc]] PegasusConfig

docs/source/en/model_doc/pegasus_x.mdx

@@ -28,6 +28,11 @@ Tips:
 
 This model was contributed by [zphang](<https://huggingface.co/zphang). The original code can be found [here](https://github.com/google-research/pegasus).
 
+## Documentation resources
+
+- [Translation task guide](./tasks/translation)
+- [Summarization task guide](./tasks/summarization)
+
 ## PegasusXConfig
 
 [[autodoc]] PegasusXConfig

docs/source/en/model_doc/perceiver.mdx

@@ -90,6 +90,12 @@ audio classification, video classification, etc.
 
 - Perceiver does **not** work with `torch.nn.DataParallel` due to a bug in PyTorch, see [issue #36035](https://github.com/pytorch/pytorch/issues/36035)
 
+## Documentation resources
+
+- [Text classification task guide](./tasks/sequence_classification)
+- [Masked language modeling task guide](./tasks/masked_language_modeling)
+- [Image classification task guide](./tasks/image_classification)
+
 ## Perceiver specific outputs
 
 [[autodoc]] models.perceiver.modeling_perceiver.PerceiverModelOutput