dataset-evaluation

1# Workflow Instruction
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3Follow the workflow shown below. Locate the dataset, check the file type, and resolve any issues with missing files or wrong file types. Determine the fine-tuning model and fine-tuning strategy. Run the appropriate validation based on the model family. Summarize the results: is the dataset ready for fine-tuning?
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5## Prerequisites
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7- The SDK environment has been verified (SDK version, region, execution role). If not done, activate the `sdk-getting-started` skill first.
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11## Workflow
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131. **Locate Dataset**:
14   - The full path may be a local file path, or an S3 URI
15   - Resolve the full path to the dataset file, make sure read permissions are available, and help the user if the file is not found
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172. **Determine strategy and model**:
18   - File formatting depends on the currently selected fine-tuning strategy and fine-tuning base model.
19   - If the strategy and model are already known from the conversation context (e.g., selected via the model-selection and finetuning-technique skills), use them.
20   - If not available in context, activate the model-selection and/or finetuning-technique skills to determine them before proceeding.
21   - **Exception:** If the user is validating an evaluation dataset (not a training dataset), neither model nor technique is required — the format detector can validate eval format (query/response structure) independently. Do not block on model-selection or finetuning-technique for eval dataset validation.
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