Fix example usage

README.md

@@ -21,6 +21,7 @@ The original tokenizer is supposed to be used (i.e. `tokenizer.model` in [GitHub
 ```python
 import torch
 from transformers import AutoModelForCausalLM
+from sentencepiece import SentencePieceProcessor
 
 torch.set_default_dtype(torch.bfloat16)
 model = AutoModelForCausalLM.from_pretrained(
@@ -44,5 +45,13 @@ inputs = {
 outputs = model.generate(**inputs)
 ```
 
+You could also use the transformers-compatible version of the tokenizer [Xenova/grok-1-tokenizer](https://huggingface.co/Xenova/grok-1-tokenizer) 
+```python
+from transformers import LlamaTokenizerFast
+
+tokenizer = LlamaTokenizerFast.from_pretrained('Xenova/grok-1-tokenizer')
+inputs = tokenizer('hello world')
+```
+
 
 Note: A multi-GPU machine is required to test the model with the example code (For now, a 8x80G multi-GPU machine is required).