fix checkpoint name for wav2vec2 conformer (#18994)

* fix checkpoint name for wav2vec2 conformer Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
huggingface · Sep 12, 2022 · 39b5bb7 · 39b5bb7
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diff --git a/src/transformers/models/wav2vec2_conformer/configuration_wav2vec2_conformer.py b/src/transformers/models/wav2vec2_conformer/configuration_wav2vec2_conformer.py
@@ -24,8 +24,8 @@
 logger = logging.get_logger(__name__)
 
 WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP = {
-    "facebook/wav2vec2-conformer-large-rel-pos": (
-        "https://huggingface.co/facebook/wav2vec2-conformer-large-rel-pos/resolve/main/config.json"
+    "facebook/wav2vec2-conformer-rel-pos-large": (
+        "https://huggingface.co/facebook/wav2vec2-conformer-rel-pos-large/resolve/main/config.json"
     ),
 }
 
@@ -35,7 +35,7 @@ class Wav2Vec2ConformerConfig(PretrainedConfig):
     This is the configuration class to store the configuration of a [`Wav2Vec2ConformerModel`]. It is used to
     instantiate an Wav2Vec2Conformer 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 Wav2Vec2Conformer
-    [facebook/wav2vec2-conformer-large-rel-pos](https://huggingface.co/facebook/wav2vec2-conformer-large-rel-pos)
+    [facebook/wav2vec2-conformer-rel-pos-large](https://huggingface.co/facebook/wav2vec2-conformer-rel-pos-large)
     architecture.
 
     Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
@@ -195,10 +195,10 @@ class Wav2Vec2ConformerConfig(PretrainedConfig):
     ```python
     >>> from transformers import Wav2Vec2ConformerModel, Wav2Vec2ConformerConfig
 
-    >>> # Initializing a Wav2Vec2Conformer facebook/wav2vec2-conformer-large-rel-pos style configuration
+    >>> # Initializing a Wav2Vec2Conformer facebook/wav2vec2-conformer-rel-pos-large style configuration
     >>> configuration = Wav2Vec2ConformerConfig()
 
-    >>> # Initializing a model from the facebook/wav2vec2-conformer-large-rel-pos style configuration
+    >>> # Initializing a model from the facebook/wav2vec2-conformer-rel-pos-large style configuration
     >>> model = Wav2Vec2ConformerModel(configuration)
 
     >>> # Accessing the model configuration

diff --git a/src/transformers/models/wav2vec2_conformer/modeling_wav2vec2_conformer.py b/src/transformers/models/wav2vec2_conformer/modeling_wav2vec2_conformer.py
@@ -80,7 +80,7 @@
 
 
 WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST = [
-    "facebook/wav2vec2-conformer-large-rel-pos",
+    "facebook/wav2vec2-conformer-rel-pos-large",
     # See all Wav2Vec2Conformer models at https://huggingface.co/models?filter=wav2vec2-conformer
 ]
 
@@ -1226,7 +1226,7 @@ def _set_gradient_checkpointing(self, module, value=False):
 
             `attention_mask` should only be passed if the corresponding processor has `config.return_attention_mask ==
             True`. For all models whose processor has `config.return_attention_mask == False`, such as
-            [wav2vec2_conformer-base](https://huggingface.co/facebook/wav2vec2-conformer-large-rel-pos),
+            [wav2vec2-conformer-rel-pos-large](https://huggingface.co/facebook/wav2vec2-conformer-rel-pos-large),
             `attention_mask` should **not** be passed to avoid degraded performance when doing batched inference. For
             such models `input_values` should simply be padded with 0 and passed without `attention_mask`. Be aware
             that these models also yield slightly different results depending on whether `input_values` is padded or