chore: import upstream snapshot with attribution

docs/pipeline/data/tabular.md

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+# Tabular
+
+![pipeline](../../images/pipeline.png#only-light)
+![pipeline](../../images/pipeline-dark.png#only-dark)
+
+The Tabular pipeline splits tabular data into rows and columns. The tabular pipeline is most useful in creating (id, text, tag) tuples to load into Embedding indexes. 
+
+## Example
+
+The following shows a simple example using this pipeline.
+
+```python
+from txtai.pipeline import Tabular
+
+# Create and run pipeline
+tabular = Tabular("id", ["text"])
+tabular("path to csv file")
+```
+
+See the link below for a more detailed example.
+
+| Notebook  | Description  |       |
+|:----------|:-------------|------:|
+| [Transform tabular data with composable workflows](https://github.com/neuml/txtai/blob/master/examples/22_Transform_tabular_data_with_composable_workflows.ipynb) | Transform, index and search tabular data | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/neuml/txtai/blob/master/examples/22_Transform_tabular_data_with_composable_workflows.ipynb) |
+
+## Configuration-driven example
+
+Pipelines are run with Python or configuration. Pipelines can be instantiated in [configuration](../../../api/configuration/#pipeline) using the lower case name of the pipeline. Configuration-driven pipelines are run with [workflows](../../../workflow/#configuration-driven-example) or the [API](../../../api#local-instance).
+
+### config.yml
+```yaml
+# Create pipeline using lower case class name
+tabular:
+    idcolumn: id
+    textcolumns:
+      - text
+
+# Run pipeline with workflow
+workflow:
+  tabular:
+    tasks:
+      - action: tabular
+```
+
+### Run with Workflows
+
+```python
+from txtai import Application
+
+# Create and run pipeline with workflow
+app = Application("config.yml")
+list(app.workflow("tabular", ["path to csv file"]))
+```
+
+### Run with API
+
+```bash
+CONFIG=config.yml uvicorn "txtai.api:app" &
+
+curl \
+  -X POST "http://localhost:8000/workflow" \
+  -H "Content-Type: application/json" \
+  -d '{"name":"tabular", "elements":["path to csv file"]}'
+```
+
+## Methods
+
+Python documentation for the pipeline.
+
+### ::: txtai.pipeline.Tabular.__init__
+### ::: txtai.pipeline.Tabular.__call__