Translate en/model_doc to JP (#27264)

* Add `model_docs`

* Add

* Update Model adoc

* Update docs/source/ja/model_doc/bark.md

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* Update docs/source/ja/model_doc/beit.md

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* Update docs/source/ja/model_doc/bit.md

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* Update docs/source/ja/model_doc/blenderbot.md

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* Update docs/source/ja/model_doc/blenderbot-small.md

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* update reiew-1

* Update toctree.yml

* translating docs and fixes of PR #27401

* Update docs/source/ja/model_doc/bert.md

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* Update docs/source/ja/model_doc/bert-generation.md

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* Update the model docs

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Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

docs/source/ja/model_doc/altclip.md

@@ -52,8 +52,8 @@ Transformerエンコーダーに画像を与えるには、各画像を固定サ
 >>> inputs = processor(text=["a photo of a cat", "a photo of a dog"], images=image, return_tensors="pt", padding=True)
 
 >>> outputs = model(**inputs)
->>> logits_per_image = outputs.logits_per_image  # これは画像-テキスト類似度スコア
->>> probs = logits_per_image.softmax(dim=1)  # Softmaxを取ることで各ラベルの確率を得られる
+>>> logits_per_image = outputs.logits_per_image  # this is the image-text similarity score
+>>> probs = logits_per_image.softmax(dim=1)  # we can take the softmax to get the label probabilities
 ```
 
 <Tip>