Improve Components and Documentation doc in README.md.

[PhilipMay]

we do not want to maintain all the links. must be easier.

[PhilipMay]

Add the doc to the sphinx page.

see old text

[`from mltb2.somajo import SoMaJoSentenceSplitter`](https://telekom.github.io/mltb2/api-reference/somajo.html#mltb2.somajo.SoMaJoSentenceSplitter)\
Split texts into sentences. For German and English language.
This is done with the [SoMaJo](https://github.com/tsproisl/SoMaJo) tool.

[`from mltb2.somajo import JaccardSimilarity`](https://telekom.github.io/mltb2/api-reference/somajo.html#mltb2.somajo.JaccardSimilarity)\
Calculate the [jaccard similarity](https://en.wikipedia.org/wiki/Jaccard_index).

[`from mltb2.transformers import TransformersTokenCounter`](https://telekom.github.io/mltb2/api-reference/transformers.html#mltb2.transformers.TransformersTokenCounter)\
Count tokens made by a [Transformers](https://github.com/huggingface/transformers) tokenizer.

[`from mltb2.somajo_transformers import TextSplitter`](https://telekom.github.io/mltb2/api-reference/somajo_transformers.html#mltb2.somajo_transformers.TextSplitter)\
Split the text into sections with a specified maximum token length.
Does not divide words, but always whole sentences.

[`from mltb2.optuna import SignificanceRepeatedTrainingPruner`](https://telekom.github.io/mltb2/api-reference/optuna.html#mltb2.optuna.SignificanceRepeatedTrainingPruner)\
An [Optuna pruner](https://optuna.readthedocs.io/en/stable/reference/pruners.html)
to use statistical significance (a t-test which serves as a heuristic) to stop
unpromising trials early, avoiding unnecessary repeated training during cross validation.