dataset-evaluation

# Workflow Instruction Follow 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 scripts/format_detector.py to evaluate whether the file is formatted correctly for the currently selected model and strategy. Summarize the results: is the dataset ready for fine-tuning? ## Workflow 1. **Locate Dataset**: - The full path may be a local file path, or an S3 URI - Resolve the full path to the dataset file, make sure read permissions are available, and help the user if the file is not found 2. **Determine strategy and model**: - File formatting depends on the currently selected fine-tuning strategy and fine-tuning base model. - If the strategy and model are already known from the conversation context (e.g., selected via the finetuning-setup skill), use them. - If not available in context, activate the finetuning-setup skill to determine them before proceeding. 3. **Check File Formatting**: Run the tool format_detector.py to make sure the file conforms to formatting requirements. - Send the full path directly to the format_detector script as an argument - Do not send the model and strategy as arguments - Do not download data from S3 - Do not make local copies of data 4. **Summarize Results**: Tell the user if their data is ready - Examine the output of format_detector and compare to the known strategy and model...