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README.md

@@ -1,39 +1,44 @@
 ---
-dataset_info:
-  features:
-  - name: id
-    dtype: string
-  - name: question
-    dtype: string
-  - name: background_text
-    dtype: string
-  - name: options
-    sequence: string
-  - name: image
-    struct:
-    - name: bytes
-      dtype: binary
-    - name: path
-      dtype: string
-  - name: answer
-    dtype: int64
-  - name: answer_type
-    dtype: int64
-  - name: explanation
-    dtype: string
-  - name: language
-    dtype: string
-  - name: instruction_following_prompt
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 722508810
-    num_examples: 1818
-  download_size: 266399881
-  dataset_size: 722508810
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
+language:
+- en
+- ja
+task_categories:
+- visual-question-answering
+- image-to-text
+pretty_name: Mecha Ja (English Translation)
+tags:
+- multimodal
+- translation
+- llm-jp-eval-mm
 ---
+
+# Mecha Ja (English Translation)
+
+This is an English translation of the [llm-jp/MECHA-ja](https://huggingface.co/datasets/llm-jp/MECHA-ja) dataset, 
+translated using [plamo-translate](https://huggingface.co/pfnet/plamo-translate).
+
+## Dataset Description
+
+This dataset is part of the [llm-jp-eval-mm](https://github.com/llm-jp/llm-jp-eval-mm) benchmark suite.
+The original Japanese questions and answers have been translated to English while preserving the visual content.
+
+### Translation Details
+
+- **Translation Model**: pfnet/plamo-translate
+- **Fields Translated**: prompt, completion, instruction
+- **Original Language**: Japanese
+- **Target Language**: English
+
+## Usage
+
+You can use this dataset with the llm-jp-eval-mm framework by specifying the language parameter:
+
+```python
+from eval_mm.tasks import MechaJa
+
+# Use English version
+task = MechaJa(language="en")
+
+# Use original Japanese version
+task = MechaJa(language="ja")
+```