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chore: update README (#13)

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Signed-off-by: Panos Vagenas <35837085+vagenas@users.noreply.github.com>
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<p align="center">
<a href="https://github.com/ds4sd/docling"> <img loading="lazy" alt="Docling" src="https://github.com/DS4SD/docling/raw/main/logo.png" width="150" />
<a href="https://github.com/ds4sd/docling">
<img loading="lazy" alt="Docling" src="https://github.com/DS4SD/docling/raw/main/logo.png" width="150" />
</a>
</p>
# Docling
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[![Imports: isort](https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336)](https://pycqa.github.io/isort/)
[![Pydantic v2](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/pydantic/pydantic/main/docs/badge/v2.json)](https://pydantic.dev)
[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
[![License MIT](https://img.shields.io/github/license/ds4sd/deepsearch-toolkit)](https://opensource.org/licenses/MIT)
[![License MIT](https://img.shields.io/github/license/DS4SD/docling)](https://opensource.org/licenses/MIT)
Docling bundles PDF document conversion to JSON and Markdown in an easy, self-contained package.
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### Adjust pipeline features
**Control pipeline options**
#### Control pipeline options
You can control if table structure recognition or OCR should be performed by arguments passed to `DocumentConverter`:
```python
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)
```
**Control table extraction options**
#### Control table extraction options
You can control if table structure recognition should map the recognized structure back to PDF cells (default) or use text cells from the structure prediction itself.
This can improve output quality if you find that multiple columns in extracted tables are erroneously merged into one.
```python
pipeline_options = PipelineOptions(do_table_structure=True)
pipeline_options.table_structure_options.do_cell_matching = False # Uses text cells predicted from table structure model
pipeline_options.table_structure_options.do_cell_matching = False # uses text cells predicted from table structure model
doc_converter = DocumentConverter(
artifacts_path=artifacts_path,