Unverified Commit eefae413 authored by Francisco Kurucz's avatar Francisco Kurucz Committed by GitHub
Browse files

Fix link to table transformer detection microsoft model (#20560)

* Fix link to table transformer detection microsoft model

* Fix doc styles
parent d5af5a0c
...@@ -27,8 +27,8 @@ from ...utils import logging ...@@ -27,8 +27,8 @@ from ...utils import logging
logger = logging.get_logger(__name__) logger = logging.get_logger(__name__)
TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP = { TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP = {
"microsoft/table-transformer-table-detection": ( "microsoft/table-transformer-detection": (
"https://huggingface.co/microsoft/table-transformer-table-detection/resolve/main/config.json" "https://huggingface.co/microsoft/table-transformer-detection/resolve/main/config.json"
), ),
} }
...@@ -38,8 +38,7 @@ class TableTransformerConfig(PretrainedConfig): ...@@ -38,8 +38,7 @@ class TableTransformerConfig(PretrainedConfig):
This is the configuration class to store the configuration of a [`TableTransformerModel`]. It is used to This is the configuration class to store the configuration of a [`TableTransformerModel`]. It is used to
instantiate a Table Transformer model according to the specified arguments, defining the model architecture. instantiate a Table Transformer model according to the specified arguments, defining the model architecture.
Instantiating a configuration with the defaults will yield a similar configuration to that of the Table Transformer Instantiating a configuration with the defaults will yield a similar configuration to that of the Table Transformer
[microsoft/table-transformer-table-detection](https://huggingface.co/microsoft/table-transformer-table-detection) [microsoft/table-transformer-detection](https://huggingface.co/microsoft/table-transformer-detection) architecture.
architecture.
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
documentation from [`PretrainedConfig`] for more information. documentation from [`PretrainedConfig`] for more information.
...@@ -117,10 +116,10 @@ class TableTransformerConfig(PretrainedConfig): ...@@ -117,10 +116,10 @@ class TableTransformerConfig(PretrainedConfig):
```python ```python
>>> from transformers import TableTransformerModel, TableTransformerConfig >>> from transformers import TableTransformerModel, TableTransformerConfig
>>> # Initializing a Table Transformer microsoft/table-transformer-table-detection style configuration >>> # Initializing a Table Transformer microsoft/table-transformer-detection style configuration
>>> configuration = TableTransformerConfig() >>> configuration = TableTransformerConfig()
>>> # Initializing a model from the microsoft/table-transformer-table-detection style configuration >>> # Initializing a model from the microsoft/table-transformer-detection style configuration
>>> model = TableTransformerModel(configuration) >>> model = TableTransformerModel(configuration)
>>> # Accessing the model configuration >>> # Accessing the model configuration
......
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