[WIP] Move X-MOD models to facebook organization (#21640)

Move X-MOD models to facebook org

docs/source/en/model_doc/xmod.mdx

@@ -38,7 +38,7 @@ There are two ways to specify the input language:
 ```python
 from transformers import XmodModel
 
-model = XmodModel.from_pretrained("jvamvas/xmod-base")
+model = XmodModel.from_pretrained("facebook/xmod-base")
 model.set_default_language("en_XX")
 ```
 

src/transformers/models/xmod/configuration_xmod.py

@@ -25,15 +25,15 @@ from ...utils import logging
 logger = logging.get_logger(__name__)
 
 XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP = {
-    "jvamvas/xmod-base": "https://huggingface.co/jvamvas/xmod-base/resolve/main/config.json",
-    "jvamvas/xmod-large-prenorm": "https://huggingface.co/jvamvas/xmod-large-prenorm/resolve/main/config.json",
-    "jvamvas/xmod-base-13-125k": "https://huggingface.co/jvamvas/xmod-base-13-125k/resolve/main/config.json",
-    "jvamvas/xmod-base-30-125k": "https://huggingface.co/jvamvas/xmod-base-30-125k/resolve/main/config.json",
-    "jvamvas/xmod-base-30-195k": "https://huggingface.co/jvamvas/xmod-base-30-195k/resolve/main/config.json",
-    "jvamvas/xmod-base-60-125k": "https://huggingface.co/jvamvas/xmod-base-60-125k/resolve/main/config.json",
-    "jvamvas/xmod-base-60-265k": "https://huggingface.co/jvamvas/xmod-base-60-265k/resolve/main/config.json",
-    "jvamvas/xmod-base-75-125k": "https://huggingface.co/jvamvas/xmod-base-75-125k/resolve/main/config.json",
-    "jvamvas/xmod-base-75-269k": "https://huggingface.co/jvamvas/xmod-base-75-269k/resolve/main/config.json",
+    "facebook/xmod-base": "https://huggingface.co/facebook/xmod-base/resolve/main/config.json",
+    "facebook/xmod-large-prenorm": "https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json",
+    "facebook/xmod-base-13-125k": "https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json",
+    "facebook/xmod-base-30-125k": "https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json",
+    "facebook/xmod-base-30-195k": "https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json",
+    "facebook/xmod-base-60-125k": "https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json",
+    "facebook/xmod-base-60-265k": "https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json",
+    "facebook/xmod-base-75-125k": "https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json",
+    "facebook/xmod-base-75-269k": "https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json",
 }
 
 
@@ -41,7 +41,7 @@ class XmodConfig(PretrainedConfig):
     r"""
     This is the configuration class to store the configuration of a [`XmodModel`]. It is used to instantiate an X-MOD
     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 [xmod-base](https://huggingface.co/jvamvas/xmod-base)
+    defaults will yield a similar configuration to that of the [xmod-base](https://huggingface.co/facebook/xmod-base)
     architecture.
 
     Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
@@ -110,10 +110,10 @@ class XmodConfig(PretrainedConfig):
     ```python
     >>> from transformers import XmodConfig, XmodModel
 
-    >>> # Initializing an X-MOD jvamvas/xmod-base style configuration
+    >>> # Initializing an X-MOD facebook/xmod-base style configuration
     >>> configuration = XmodConfig()
 
-    >>> # Initializing a model (with random weights) from the jvamvas/xmod-base style configuration
+    >>> # Initializing a model (with random weights) from the facebook/xmod-base style configuration
     >>> model = XmodModel(configuration)
 
     >>> # Accessing the model configuration

src/transformers/models/xmod/modeling_xmod.py

@@ -42,15 +42,15 @@ from .configuration_xmod import XmodConfig
 logger = logging.get_logger(__name__)
 
 XMOD_PRETRAINED_MODEL_ARCHIVE_LIST = [
-    "jvamvas/xmod-base",
-    "jvamvas/xmod-large-prenorm",
-    "jvamvas/xmod-base-13-125k",
-    "jvamvas/xmod-base-30-125k",
-    "jvamvas/xmod-base-30-195k",
-    "jvamvas/xmod-base-60-125k",
-    "jvamvas/xmod-base-60-265k",
-    "jvamvas/xmod-base-75-125k",
-    "jvamvas/xmod-base-75-269k",
+    "facebook/xmod-base",
+    "facebook/xmod-large-prenorm",
+    "facebook/xmod-base-13-125k",
+    "facebook/xmod-base-30-125k",
+    "facebook/xmod-base-30-195k",
+    "facebook/xmod-base-60-125k",
+    "facebook/xmod-base-60-265k",
+    "facebook/xmod-base-75-125k",
+    "facebook/xmod-base-75-269k",
     # See all X-MOD models at https://huggingface.co/models?filter=xmod
 ]
 
@@ -1069,9 +1069,9 @@ class XmodForCausalLM(XmodPreTrainedModel):
         >>> import torch
 
         >>> tokenizer = AutoTokenizer.from_pretrained("xlm-roberta-base")
-        >>> config = AutoConfig.from_pretrained("jvamvas/xmod-base")
+        >>> config = AutoConfig.from_pretrained("facebook/xmod-base")
         >>> config.is_decoder = True
-        >>> model = XmodForCausalLM.from_pretrained("jvamvas/xmod-base", config=config)
+        >>> model = XmodForCausalLM.from_pretrained("facebook/xmod-base", config=config)
         >>> model.set_default_language("en_XX")
 
         >>> inputs = tokenizer("Hello, my dog is cute", return_tensors="pt")

tests/models/xmod/test_modeling_xmod.py

@@ -512,7 +512,7 @@ class XmodModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase):
 class XmodModelIntegrationTest(unittest.TestCase):
     @slow
     def test_xmod_base(self):
-        model = XmodModel.from_pretrained("jvamvas/xmod-base")
+        model = XmodModel.from_pretrained("facebook/xmod-base")
 
         # language en_XX
         model.set_default_language("en_XX")
@@ -545,7 +545,7 @@ class XmodModelIntegrationTest(unittest.TestCase):
 
     @slow
     def test_xmod_large_prenorm(self):
-        model = XmodModel.from_pretrained("jvamvas/xmod-large-prenorm")
+        model = XmodModel.from_pretrained("facebook/xmod-large-prenorm")
 
         # language en_XX
         model.set_default_language("en_XX")
@@ -581,7 +581,7 @@ class XmodModelIntegrationTest(unittest.TestCase):
 
     @slow
     def test_multilingual_batch(self):
-        model = XmodModel.from_pretrained("jvamvas/xmod-base")
+        model = XmodModel.from_pretrained("facebook/xmod-base")
         # fmt: off
         input_ids = torch.tensor([
             [0, 581, 10269, 83, 99942, 136, 60742, 23, 70, 80583, 18276, 2],
@@ -608,7 +608,7 @@ class XmodModelIntegrationTest(unittest.TestCase):
     @slow
     def test_end_to_end_mask_fill(self):
         tokenizer = XLMRobertaTokenizer.from_pretrained("xlm-roberta-base")
-        model = XmodForMaskedLM.from_pretrained("jvamvas/xmod-base", default_language="en_XX")
+        model = XmodForMaskedLM.from_pretrained("facebook/xmod-base", default_language="en_XX")
         model.to(torch_device)
 
         sentences = [