Add _CHECKPOINT_FOR_DOC to all models (#12811)

* Add _CHECKPOINT_FOR_DOC

* Update src/transformers/models/funnel/modeling_funnel.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

src/transformers/models/blenderbot/modeling_blenderbot.py

@@ -51,6 +51,7 @@ logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "BlenderbotConfig"
 _TOKENIZER_FOR_DOC = "BlenderbotTokenizer"
+_CHECKPOINT_FOR_DOC = "facebook/blenderbot-400M-distill"
 
 
 BLENDERBOT_PRETRAINED_MODEL_ARCHIVE_LIST = [

src/transformers/models/blenderbot_small/modeling_blenderbot_small.py

@@ -48,6 +48,7 @@ logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "BlenderbotSmallConfig"
 _TOKENIZER_FOR_DOC = "BlenderbotSmallTokenizer"
+_CHECKPOINT_FOR_DOC = "facebook/blenderbot_small-90M"
 
 
 BLENDERBOT_SMALL_PRETRAINED_MODEL_ARCHIVE_LIST = [

src/transformers/models/clip/modeling_clip.py

@@ -36,6 +36,7 @@ from .configuration_clip import CLIPConfig, CLIPTextConfig, CLIPVisionConfig
 
 logger = logging.get_logger(__name__)
 
+_CHECKPOINT_FOR_DOC = "openai/clip-vit-base-patch32"
 
 CLIP_PRETRAINED_MODEL_ARCHIVE_LIST = [
     "openai/clip-vit-base-patch32",

src/transformers/models/deit/modeling_deit.py

@@ -41,6 +41,7 @@ from .configuration_deit import DeiTConfig
 logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "DeiTConfig"
+_CHECKPOINT_FOR_DOC = "facebook/deit-base-distilled-patch16-224"
 
 DEIT_PRETRAINED_MODEL_ARCHIVE_LIST = [
     "facebook/deit-base-distilled-patch16-224",

src/transformers/models/detr/modeling_detr.py

@@ -52,6 +52,7 @@ if is_timm_available():
 logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "DetrConfig"
+_CHECKPOINT_FOR_DOC = "facebook/detr-resnet-50"
 
 DETR_PRETRAINED_MODEL_ARCHIVE_LIST = [
     "facebook/detr-resnet-50",

src/transformers/models/dpr/modeling_dpr.py

@@ -37,6 +37,7 @@ from .configuration_dpr import DPRConfig
 logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "DPRConfig"
+_CHECKPOINT_FOR_DOC = "facebook/dpr-ctx_encoder-single-nq-base"
 
 DPR_CONTEXT_ENCODER_PRETRAINED_MODEL_ARCHIVE_LIST = [
     "facebook/dpr-ctx_encoder-single-nq-base",

src/transformers/models/funnel/modeling_funnel.py

@@ -48,6 +48,7 @@ logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "FunnelConfig"
 _TOKENIZER_FOR_DOC = "FunnelTokenizer"
+_CHECKPOINT_FOR_DOC = "funnel-transformer/small"
 
 FUNNEL_PRETRAINED_MODEL_ARCHIVE_LIST = [
     "funnel-transformer/small",  # B4-4-4H768
@@ -987,7 +988,7 @@ class FunnelModel(FunnelPreTrainedModel):
     @add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
     @add_code_sample_docstrings(
         tokenizer_class=_TOKENIZER_FOR_DOC,
-        checkpoint="funnel-transformer/small",
+        checkpoint=_CHECKPOINT_FOR_DOC,
         output_type=BaseModelOutput,
         config_class=_CONFIG_FOR_DOC,
     )
@@ -1174,7 +1175,7 @@ class FunnelForMaskedLM(FunnelPreTrainedModel):
     @add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
     @add_code_sample_docstrings(
         tokenizer_class=_TOKENIZER_FOR_DOC,
-        checkpoint="funnel-transformer/small",
+        checkpoint=_CHECKPOINT_FOR_DOC,
         output_type=MaskedLMOutput,
         config_class=_CONFIG_FOR_DOC,
         mask="<mask>",
@@ -1424,7 +1425,7 @@ class FunnelForTokenClassification(FunnelPreTrainedModel):
     @add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
     @add_code_sample_docstrings(
         tokenizer_class=_TOKENIZER_FOR_DOC,
-        checkpoint="funnel-transformer/small",
+        checkpoint=_CHECKPOINT_FOR_DOC,
         output_type=TokenClassifierOutput,
         config_class=_CONFIG_FOR_DOC,
     )
@@ -1506,7 +1507,7 @@ class FunnelForQuestionAnswering(FunnelPreTrainedModel):
     @add_start_docstrings_to_model_forward(FUNNEL_INPUTS_DOCSTRING.format("batch_size, sequence_length"))
     @add_code_sample_docstrings(
         tokenizer_class=_TOKENIZER_FOR_DOC,
-        checkpoint="funnel-transformer/small",
+        checkpoint=_CHECKPOINT_FOR_DOC,
         output_type=QuestionAnsweringModelOutput,
         config_class=_CONFIG_FOR_DOC,
     )

src/transformers/models/hubert/modeling_hubert.py

@@ -34,6 +34,7 @@ from .configuration_hubert import HubertConfig
 logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "HubertConfig"
+_CHECKPOINT_FOR_DOC = "facebook/hubert-base-ls960"
 
 HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST = [
     "facebook/hubert-base-ls960",

src/transformers/models/layoutlm/modeling_layoutlm.py

@@ -45,6 +45,7 @@ logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "LayoutLMConfig"
 _TOKENIZER_FOR_DOC = "LayoutLMTokenizer"
+_CHECKPOINT_FOR_DOC = "microsoft/layoutlm-base-uncased"
 
 LAYOUTLM_PRETRAINED_MODEL_ARCHIVE_LIST = [
     "layoutlm-base-uncased",

src/transformers/models/luke/modeling_luke.py

@@ -39,6 +39,7 @@ logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "LukeConfig"
 _TOKENIZER_FOR_DOC = "LukeTokenizer"
+_CHECKPOINT_FOR_DOC = "studio-ousia/luke-base"
 
 LUKE_PRETRAINED_MODEL_ARCHIVE_LIST = [
     "studio-ousia/luke-base",

src/transformers/models/m2m_100/modeling_m2m_100.py

@@ -46,6 +46,7 @@ logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "M2M100Config"
 _TOKENIZER_FOR_DOC = "M2M100Tokenizer"
+_CHECKPOINT_FOR_DOC = "facebook/m2m100_418M"
 
 
 M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST = [
@@ -1117,7 +1118,7 @@ class M2M100Model(M2M100PreTrainedModel):
     @add_start_docstrings_to_model_forward(M2M_100_INPUTS_DOCSTRING)
     @add_code_sample_docstrings(
         tokenizer_class=_TOKENIZER_FOR_DOC,
-        checkpoint="facebook/m2m100_418M",
+        checkpoint=_CHECKPOINT_FOR_DOC,
         output_type=Seq2SeqModelOutput,
         config_class=_CONFIG_FOR_DOC,
     )

src/transformers/models/marian/modeling_marian.py

@@ -49,6 +49,7 @@ logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "MarianConfig"
 _TOKENIZER_FOR_DOC = "MarianTokenizer"
+_CHECKPOINT_FOR_DOC = "Helsinki-NLP/opus-mt-en-de"
 
 
 MARIAN_PRETRAINED_MODEL_ARCHIVE_LIST = [

src/transformers/models/prophetnet/modeling_prophetnet.py

@@ -42,6 +42,7 @@ logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "ProphenetConfig"
 _TOKENIZER_FOR_DOC = "ProphetNetTokenizer"
+_CHECKPOINT_FOR_DOC = "microsoft/prophetnet-large-uncased"
 
 PROPHETNET_PRETRAINED_MODEL_ARCHIVE_LIST = [
     "microsoft/prophetnet-large-uncased",

src/transformers/models/speech_to_text/modeling_speech_to_text.py

@@ -45,6 +45,7 @@ logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "Speech2TextConfig"
 _TOKENIZER_FOR_DOC = "Speech2TextTokenizer"
+_CHECKPOINT_FOR_DOC = "facebook/s2t-small-librispeech-asr"
 
 
 SPEECH_TO_TEXT_PRETRAINED_MODEL_ARCHIVE_LIST = [
@@ -1131,7 +1132,7 @@ class Speech2TextModel(Speech2TextPreTrainedModel):
     @add_start_docstrings_to_model_forward(SPEECH_TO_TEXT_INPUTS_DOCSTRING)
     @add_code_sample_docstrings(
         tokenizer_class=_TOKENIZER_FOR_DOC,
-        checkpoint="s2t_transformer_s",
+        checkpoint=_CHECKPOINT_FOR_DOC,
         output_type=Seq2SeqModelOutput,
         config_class=_CONFIG_FOR_DOC,
     )

src/transformers/models/t5/modeling_t5.py

@@ -50,6 +50,7 @@ logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "T5Config"
 _TOKENIZER_FOR_DOC = "T5Tokenizer"
+_CHECKPOINT_FOR_DOC = "t5-small"
 
 ####################################################
 # This dict contains ids and associated url

src/transformers/models/tapas/modeling_tapas.py

@@ -54,6 +54,7 @@ logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "TapasConfig"
 _TOKENIZER_FOR_DOC = "TapasTokenizer"
+_TOKENIZER_FOR_DOC = "google/tapas-base"
 
 TAPAS_PRETRAINED_MODEL_ARCHIVE_LIST = [
     # large models

src/transformers/models/visual_bert/modeling_visual_bert.py

@@ -50,6 +50,7 @@ from .configuration_visual_bert import VisualBertConfig
 logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "VisualBertConfig"
+_CHECKPOINT_FOR_DOC = "uclanlp/visualbert-vqa-coco-pre"
 
 VISUAL_BERT_PRETRAINED_MODEL_ARCHIVE_LIST = [
     "uclanlp/visualbert-vqa",

src/transformers/models/vit/modeling_vit.py

@@ -34,9 +34,10 @@ from .configuration_vit import ViTConfig
 logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "ViTConfig"
+_CHECKPOINT_FOR_DOC = "google/vit-base-patch16-224"
 
 VIT_PRETRAINED_MODEL_ARCHIVE_LIST = [
-    "nielsr/vit-base-patch16-224",
+    "google/vit-base-patch16-224",
     # See all ViT models at https://huggingface.co/models?filter=vit
 ]
 

src/transformers/models/wav2vec2/modeling_wav2vec2.py

@@ -40,6 +40,7 @@ from .configuration_wav2vec2 import Wav2Vec2Config
 logger = logging.get_logger(__name__)
 
 _CONFIG_FOR_DOC = "Wav2Vec2Config"
+_CHECKPOINT_FOR_DOC = "facebook/wav2vec2-base-960h"
 
 WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST = [
     "facebook/wav2vec2-base-960h",