Update README.md

README.md

@@ -71,10 +71,10 @@ Find below some example scripts on how to use the model in `transformers`:
 
 ```python
 
-from transformers import AutoTokenizer, SwitchTransformersConditionalGeneration
+from transformers import AutoTokenizer, SwitchTransformersForConditionalGeneration
 
 tokenizer = AutoTokenizer.from_pretrained("google/switch-base-32")
-model = SwitchTransformersConditionalGeneration.from_pretrained("google/switch-base-32")
+model = SwitchTransformersForConditionalGeneration.from_pretrained("google/switch-base-32")
 
 input_text = "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids
@@ -93,10 +93,10 @@ print(tokenizer.decode(outputs[0]))
 
 ```python
 # pip install accelerate
-from transformers import AutoTokenizer, SwitchTransformersConditionalGeneration
+from transformers import AutoTokenizer, SwitchTransformersForConditionalGeneration
 
 tokenizer = AutoTokenizer.from_pretrained("google/switch-base-32")
-model = SwitchTransformersConditionalGeneration.from_pretrained("google/switch-base-32", device_map="auto")
+model = SwitchTransformersForConditionalGeneration.from_pretrained("google/switch-base-32", device_map="auto")
 
 input_text = "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(0)
@@ -117,10 +117,10 @@ print(tokenizer.decode(outputs[0]))
 
 ```python
 # pip install accelerate
-from transformers import AutoTokenizer, SwitchTransformersConditionalGeneration
+from transformers import AutoTokenizer, SwitchTransformersForConditionalGeneration
 
 tokenizer = AutoTokenizer.from_pretrained("google/switch-base-32")
-model = SwitchTransformersConditionalGeneration.from_pretrained("google/switch-base-32", device_map="auto", torch_dtype=torch.float16)
+model = SwitchTransformersForConditionalGeneration.from_pretrained("google/switch-base-32", device_map="auto", torch_dtype=torch.float16)
 
 input_text = "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(0)
@@ -139,10 +139,10 @@ print(tokenizer.decode(outputs[0]))
 
 ```python
 # pip install bitsandbytes accelerate
-from transformers import AutoTokenizer, SwitchTransformersConditionalGeneration
+from transformers import AutoTokenizer, SwitchTransformersForConditionalGeneration
 
 tokenizer = AutoTokenizer.from_pretrained("google/switch-base-32")
-model = SwitchTransformersConditionalGeneration.from_pretrained("google/switch-base-32", device_map="auto")
+model = SwitchTransformersForConditionalGeneration.from_pretrained("google/switch-base-32", device_map="auto")
 
 input_text = "A <extra_id_0> walks into a bar a orders a <extra_id_1> with <extra_id_2> pinch of <extra_id_3>."
 input_ids = tokenizer(input_text, return_tensors="pt").input_ids.to(0)