updated generation

README.md

@@ -58,16 +58,6 @@ outputs = model.generate(inputs)
 print(tokenizer.decode(outputs[0]))
 ```
 
-### Fill-in-the-middle
-Fill-in-the-middle uses special tokens to identify the prefix/middle/suffix part of the input and output:
-
-```Java
-input_text = "<fim_prefix>public class HelloWorld {\n    public static void main(String[] args) {<fim_suffix>}\n}<fim_middle>"
-inputs = tokenizer.encode(input_text, return_tensors="pt").to(device)
-outputs = model.generate(inputs)
-print(tokenizer.decode(outputs[0]))
-```
-
 ### Attribution & Other Requirements
 
 The pretraining dataset of the model was filtered for permissive licenses only. Nevertheless, the model can generate source code verbatim from the dataset. The code's license might require attribution and/or other specific requirements that must be respected. We provide a [search index](https://huggingface.co/spaces/bigcode/starcoder-search) that let's you search through the pretraining data to identify where generated code came from and apply the proper attribution to your code.