Update README.md

README.md

@@ -42,8 +42,8 @@ First make sure to `pip install -U transformers`, then copy the snippet from the
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
-tokenizer = AutoTokenizer.from_pretrained("yam-peleg/Hebrew-Gemma-11B")
-model = AutoModelForCausalLM.from_pretrained("yam-peleg/Hebrew-Gemma-11B")
+tokenizer = AutoTokenizer.from_pretrained("yam-peleg/Hebrew-Gemma-11B-V2")
+model = AutoModelForCausalLM.from_pretrained("yam-peleg/Hebrew-Gemma-11B-V2")
 
 input_text = "שלום! מה שלומך היום?"
 input_ids = tokenizer(input_text, return_tensors="pt")
@@ -57,8 +57,8 @@ print(tokenizer.decode(outputs[0]))
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM
 
-tokenizer = AutoTokenizer.from_pretrained("yam-peleg/Hebrew-Gemma-11B")
-model = AutoModelForCausalLM.from_pretrained("yam-peleg/Hebrew-Gemma-11B", device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("yam-peleg/Hebrew-Gemma-11B-V2")
+model = AutoModelForCausalLM.from_pretrained("yam-peleg/Hebrew-Gemma-11B-V2", device_map="auto")
 
 input_text = "שלום! מה שלומך היום?"
 input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
@@ -72,8 +72,8 @@ print(tokenizer.decode(outputs[0]))
 ```python
 from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
 
-tokenizer = AutoTokenizer.from_pretrained("yam-peleg/Hebrew-Gemma-11B")
-model = AutoModelForCausalLM.from_pretrained("yam-peleg/Hebrew-Gemma-11B", quantization_config = BitsAndBytesConfig(load_in_4bit=True))
+tokenizer = AutoTokenizer.from_pretrained("yam-peleg/Hebrew-Gemma-11B-V2")
+model = AutoModelForCausalLM.from_pretrained("yam-peleg/Hebrew-Gemma-11B-V2", quantization_config = BitsAndBytesConfig(load_in_4bit=True))
 
 input_text = "שלום! מה שלומך היום?"
 input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")
@@ -89,7 +89,7 @@ print(tokenizer.decode(outputs[0])
 
 ### Notice
 
-Hebrew-Gemma-11B is a pretrained base model and therefore does not have any moderation mechanisms.
+Hebrew-Gemma-11B-V2 is a pretrained base model and therefore does not have any moderation mechanisms.
 
 
 ### Authors