v.0.1.0: Mixcase tasks and more 🥳

This release of TextMachina includes:

• Allow to pass parameters to the extractors out from the prompt templates. The templates must be used only to define placeholders.
• Add MixCaseDatasetGenerator to generate datasets for mixcase tasks (detection tagging). Other datasets like mixcase classification can be built out of TextMachina, using the datasets generated by this one.
• Add sentence_gap and word_gap extractors for mixcase tasks.
• Refactor interactive exploration. Now we have one class per task, and each one must build its own panels.
• Added exploration for mixcase datasets.
• Added a TokenClassificationMetric to evaluate HF models on mixcase and boundary tasks.
• Better structured and documented examples. Now we have examples/learning to illustrate how to use providers/tasks/extractors and examples/use_cases with additional config files.
• Minor changes to improve quality of life: force to pass task_type in the CLI to prevent potential confusions, disable random_sample_human on boundary detection tasks, etc.
• Document all the new code and improve existing documentation.
• Extend the README to talk about mixcase tasks, include figures to visualize each type of task.