Add missing ckpt in config docs (#16900)

* add missing ckpt in config docs

* add more missing ckpt in config docs

* fix wrong ckpts

* fix realm ckpt

* fix s2t2

* fix xlm_roberta ckpt

* Fix for deberta v2

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* use only one checkpoint for DPR

* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

src/transformers/models/van/configuration_van.py

@@ -21,7 +21,7 @@ from ...utils import logging
 logger = logging.get_logger(__name__)
 
 VAN_PRETRAINED_CONFIG_ARCHIVE_MAP = {
-    "van-base": "https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json",
+    "Visual-Attention-Network/van-base": "https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json",
 }
 
 
@@ -29,8 +29,8 @@ class VanConfig(PretrainedConfig):
     r"""
     This is the configuration class to store the configuration of a [`VanModel`]. It is used to instantiate a VAN 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 VAN [van-base](https://huggingface.co/van-base)
-    architecture.
+    defaults will yield a similar configuration to that of the VAN
+    [Visual-Attention-Network/van-base](https://huggingface.co/Visual-Attention-Network/van-base) architecture.
 
     Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
     documentation from [`PretrainedConfig`] for more information.

src/transformers/models/visual_bert/configuration_visual_bert.py

@@ -39,7 +39,7 @@ class VisualBertConfig(PretrainedConfig):
     This is the configuration class to store the configuration of a [`VisualBertModel`]. It is used to instantiate an
     VisualBERT 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 VisualBERT
-    [visualbert-vqa-coco-pre](https://huggingface.co/uclanlp/visualbert-vqa-coco-pre) architecture.
+    [uclanlp/visualbert-vqa-coco-pre](https://huggingface.co/uclanlp/visualbert-vqa-coco-pre) architecture.
 
     Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
     documentation from [`PretrainedConfig`] for more information.

src/transformers/models/wavlm/configuration_wavlm.py

@@ -24,7 +24,7 @@ from ...utils import logging
 logger = logging.get_logger(__name__)
 
 WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP = {
-    "facebook/wavlm-base-960h": "https://huggingface.co/facebook/wavlm-base-960h/resolve/main/config.json",
+    "microsoft/wavlm-base": "https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json",
     # See all WavLM models at https://huggingface.co/models?filter=wavlm
 }
 
@@ -34,7 +34,7 @@ class WavLMConfig(PretrainedConfig):
     This is the configuration class to store the configuration of a [`WavLMModel`]. It is used to instantiate an WavLM
     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 WavLM
-    [facebook/wavlm-base-960h](https://huggingface.co/facebook/wavlm-base-960h) architecture.
+    [microsoft/wavlm-base](https://huggingface.co/microsoft/wavlm-base) architecture.
 
     Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
     documentation from [`PretrainedConfig`] for more information.

src/transformers/models/xlm_prophetnet/configuration_xlm_prophetnet.py

@@ -29,7 +29,10 @@ XLM_PROPHETNET_PRETRAINED_CONFIG_ARCHIVE_MAP = {
 class XLMProphetNetConfig(ProphetNetConfig):
     """
     This class overrides [`ProphetNetConfig`]. Please check the superclass for the appropriate documentation alongside
-    usage examples.
+    usage examples. Instantiating a configuration with the defaults will yield a similar configuration to that of the
+    XLMProphetNet
+    [microsoft/xprophetnet-large-wiki100-cased](https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased)
+    architecture.
     """
 
     model_type = "xlm-prophetnet"

src/transformers/models/xlm_roberta/configuration_xlm_roberta.py

@@ -37,7 +37,8 @@ XLM_ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP = {
 class XLMRobertaConfig(RobertaConfig):
     """
     This class overrides [`RobertaConfig`]. Please check the superclass for the appropriate documentation alongside
-    usage examples.
+    usage examples. Instantiating a configuration with the defaults will yield a similar configuration to that of the
+    XLMRoBERTa [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) architecture.
     """
 
     model_type = "xlm-roberta"

src/transformers/models/xlm_roberta_xl/configuration_xlm_roberta_xl.py

@@ -25,8 +25,8 @@ from ...utils import logging
 logger = logging.get_logger(__name__)
 
 XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP = {
-    "xlm-roberta-xl": "https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json",
-    "xlm-roberta-xxl": "https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json",
+    "facebook/xlm-roberta-xl": "https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json",
+    "facebook/xlm-roberta-xxl": "https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json",
     # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
 }
 
@@ -36,7 +36,7 @@ class XLMRobertaXLConfig(PretrainedConfig):
     This is the configuration class to store the configuration of a [`XLMRobertaXLModel`] or a [`TFXLMRobertaXLModel`].
     It is used to instantiate a XLM_ROBERTA_XL 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
-    XLM_ROBERTA_XL [bert-base-uncased](https://huggingface.co/bert-base-uncased) architecture.
+    XLM_ROBERTA_XL [facebook/xlm-roberta-xl](https://huggingface.co/facebook/xlm-roberta-xl) architecture.
 
     Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
     documentation from [`PretrainedConfig`] for more information.