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Add quick start guide

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@@ -14,6 +14,31 @@ The motivation of the genomics long range benchmark (LRB) is to compile a set of
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  While serving as a strong basis of evaluation, the benchmark must also be efficient and user-friendly.
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  To achieve this we strike a balance between task complexity and computational cost through strategic decisions, such as down-sampling or combining datasets.
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  ## Dataset Tasks
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  The Genomics LRB is a collection of tasks which can be loaded by passing in the corresponding `task_name` into the `load_dataset` function. All of the following datasets
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  allow the user to specify an arbitrarily long sequence length, giving more context to the task, by passing `sequence_length` kwarg to `load_dataset`. Additional task specific kwargs, if applicable,
 
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  While serving as a strong basis of evaluation, the benchmark must also be efficient and user-friendly.
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  To achieve this we strike a balance between task complexity and computational cost through strategic decisions, such as down-sampling or combining datasets.
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+ ## Quick Start Guide
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+ Below is an example of how to use these benchmark datasets with the Huggingface `datasets` library:
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+
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+ ```python
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+ def find_variant_idx(examples):
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+ """Find token location that differs between reference and variant sequence.
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+
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+ Args:
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+ examples: (batch of) items from the dataset.
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+ Returns:
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+ dict with values index of difference.
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+ """
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+ idx = -1
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+ for i, (ref, alt) in enumerate(zip(examples["ref_input_ids"], examples["alt_input_ids"])):
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+ if ref != alt:
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+ idx = i
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+ rc_idx = -1
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+ for i, (ref, alt) in enumerate(zip(examples["ref_rc_input_ids"], examples["alt_rc_input_ids"])):
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+ if ref != alt:
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+ rc_idx = i
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+ return {"variant_idx": idx, "rc_variant_idx": rc_idx}
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+
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+ dataset = dataset.map(find_variant_idx, desc="Find variant idx")
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+ ```
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+
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  ## Dataset Tasks
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  The Genomics LRB is a collection of tasks which can be loaded by passing in the corresponding `task_name` into the `load_dataset` function. All of the following datasets
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  allow the user to specify an arbitrarily long sequence length, giving more context to the task, by passing `sequence_length` kwarg to `load_dataset`. Additional task specific kwargs, if applicable,