Update README.md

README.md

@@ -97,7 +97,35 @@ This would have the form {some prelude text here} \<INFILLING LOCATION\> {some t
 
 The way to perform infilling generation would be via placing the input text into this format:
 
-\<SUF\> {some text following cursor} \<PRE\> {some prelude text here} \<MID\> ... language model output is generated after \<MID\> token!
+\<SUF\> {some text following cursor} \<PRE\> {some prelude text here} \<MID\> ... 
+
+
+language model output is generated after \<MID\> token!
+
+
+As a concrete example, here is a code snippet that should allow a model to perform infilling:
+
+```python
+
+
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+
+tokenizer = AutoTokenizer.from_pretrained("CarperAI/FIM-NeoX-1.3B")
+model = AutoModelForCausalLM.from_pretrained("CarperAI/FIM-NeoX-1.3B")
+
+prelude = "this is some text preceding the cursor,"
+suffix = "and this is some text after it."
+
+
+model_tokenized_input = [50253, *tokenizer(suffix), 50254, *tokenizer(prefix), 50255]
+
+infilled = model.generate(model_tokenized_input)
+
+
+```
+
+We are working on making a better interface for this in future model releases or updates to the tokenizer.
 
 
 ## Intended Uses and Limitations