updating models urls

transformers/configuration_t5.py

@@ -28,6 +28,10 @@ logger = logging.getLogger(__name__)
 
 T5_PRETRAINED_CONFIG_ARCHIVE_MAP = {
     't5-small': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-small-config.json",
+    't5-base': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-base-config.json",
+    't5-large': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-large-config.json",
+    't5-3B': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-3B-config.json",
+    't5-11B': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-11B-config.json",
 }
 
 

transformers/convert_pytorch_checkpoint_to_tf2.py

@@ -121,7 +121,7 @@ def convert_pt_checkpoint_to_tf(model_type, pytorch_checkpoint_path, config_file
 
     if compare_with_pt_model:
         inputs_list = [[7, 6, 0, 0, 1], [1, 2, 3, 0, 0], [0, 0, 0, 4, 5]]
-        tf_inputs = tf.constant(inputs_list)
+        tf_inputs = tf_model.dummy_inputs
         tfo = tf_model(tf_inputs, training=False)  # build the network
 
         pt_model = pt_model_class.from_pretrained(None,

transformers/modeling_t5.py

@@ -42,6 +42,10 @@ logger = logging.getLogger(__name__)
 ####################################################
 T5_PRETRAINED_MODEL_ARCHIVE_MAP = {
     't5-small': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-small-pytorch_model.bin",
+    't5-base': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-base-pytorch_model.bin",
+    't5-large': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-large-pytorch_model.bin",
+    't5-3B': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-3B-pytorch_model.bin",
+    't5-11B': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-11B-pytorch_model.bin",
 }
 
 ####################################################

transformers/modeling_tf_t5.py

@@ -25,13 +25,17 @@ import itertools
 import tensorflow as tf
 
 from .configuration_t5 import T5Config
-from .modeling_tf_utils import TFPreTrainedModel, TFSharedEmbeddings, shape_list, get_initializer, DUMMY_INPUTS
+from .modeling_tf_utils import TFPreTrainedModel, TFSharedEmbeddings, shape_list
 from .file_utils import add_start_docstrings
 
 logger = logging.getLogger(__name__)
 
 TF_T5_PRETRAINED_MODEL_ARCHIVE_MAP = {
     't5-small': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-small-tf_model.h5",
+    't5-base': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-base-tf_model.h5",
+    't5-large': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-large-tf_model.h5",
+    't5-3B': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-3B-tf_model.h5",
+    't5-11B': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-11B-tf_model.h5",
 }
 
 ####################################################

transformers/tokenization_t5.py

@@ -41,7 +41,11 @@ VOCAB_FILES_NAMES = {'vocab_file': 'spiece.model'}
 PRETRAINED_VOCAB_FILES_MAP = {
     'vocab_file':
     {
-        't5': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-spiece.model",
+        't5-small': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-spiece.model",
+        't5-base': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-spiece.model",
+        't5-large': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-spiece.model",
+        't5-3B': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-spiece.model",
+        't5-11B': "https://s3.amazonaws.com/models.huggingface.co/bert/t5-spiece.model",
     }
 }
 
@@ -49,7 +53,11 @@ PRETRAINED_VOCAB_FILES_MAP = {
 # Mapping from model shortcut names to max length of inputs
 ####################################################
 PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES = {
-    't5': 512,
+    't5-small': 512,
+    't5-base': 512,
+    't5-large': 512,
+    't5-3B': 512,
+    't5-11B': 512,
 }
 
 class T5Tokenizer(PreTrainedTokenizer):