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Upload README.md with huggingface_hub

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@@ -24,25 +24,25 @@ jav, tha, vie
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  ## Supported Tasks
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  Question Answering, Visual Question Answering
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-
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  ## Dataset Usage
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  ### Using `datasets` library
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  ```
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- from datasets import load_dataset
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- dset = datasets.load_dataset("SEACrowd/m3exam", trust_remote_code=True)
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  ```
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  ### Using `seacrowd` library
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  ```import seacrowd as sc
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  # Load the dataset using the default config
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- dset = sc.load_dataset("m3exam", schema="seacrowd")
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  # Check all available subsets (config names) of the dataset
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- print(sc.available_config_names("m3exam"))
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  # Load the dataset using a specific config
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- dset = sc.load_dataset_by_config_name(config_name="<config_name>")
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  ```
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-
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- More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).
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-
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  ## Dataset Homepage
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  ## Supported Tasks
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  Question Answering, Visual Question Answering
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+
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  ## Dataset Usage
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  ### Using `datasets` library
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  ```
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+ from datasets import load_dataset
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+ dset = datasets.load_dataset("SEACrowd/m3exam", trust_remote_code=True)
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  ```
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  ### Using `seacrowd` library
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  ```import seacrowd as sc
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  # Load the dataset using the default config
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+ dset = sc.load_dataset("m3exam", schema="seacrowd")
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  # Check all available subsets (config names) of the dataset
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+ print(sc.available_config_names("m3exam"))
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  # Load the dataset using a specific config
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+ dset = sc.load_dataset_by_config_name(config_name="<config_name>")
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  ```
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+
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+ More details on how to load the `seacrowd` library can be found [here](https://github.com/SEACrowd/seacrowd-datahub?tab=readme-ov-file#how-to-use).
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+
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  ## Dataset Homepage
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