Update README.md

README.md

@@ -49,7 +49,7 @@ Using the model in fp16 with the text generation pipeline, here is what you can
 from transformers import pipeline
 import torch
 
-generator = pipeline(model="nlpcloud/instruct-gpt-j", torch_dtype=torch.float16, device=0)
+generator = pipeline(model="nlpcloud/instruct-gpt-j-fp16", torch_dtype=torch.float16, device=0)
 
 prompt = "Correct spelling and grammar from the following text.\nI do not wan to go\n"
 
@@ -62,8 +62,8 @@ You can also use the `generate()` function. Here is what you can do:
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 
-tokenizer = AutoTokenizer.from_pretrained('nlpcloud/instruct-gpt-j')
-generator = AutoModelForCausalLM.from_pretrained("nlpcloud/instruct-gpt-j",torch_dtype=torch.float16).cuda()
+tokenizer = AutoTokenizer.from_pretrained('nlpcloud/instruct-gpt-j-fp16')
+generator = AutoModelForCausalLM.from_pretrained("nlpcloud/instruct-gpt-j-fp16",torch_dtype=torch.float16).cuda()
 
 prompt = "Correct spelling and grammar from the following text.\nI do not wan to go\n"