More fixes for doctest (#30265)

* fix

* update

* update

* fix

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

docs/source/en/model_doc/code_llama.md

@@ -97,6 +97,7 @@ If you only want the infilled part:
 
 >>> generator = pipeline("text-generation",model="codellama/CodeLlama-7b-hf",torch_dtype=torch.float16, device_map="auto")
 >>> generator('def remove_non_ascii(s: str) -> str:\n    """ <FILL_ME>\n    return result', max_new_tokens = 128)
+[{'generated_text': 'def remove_non_ascii(s: str) -> str:\n    """ <FILL_ME>\n    return resultRemove non-ASCII characters from a string. """\n    result = ""\n    for c in s:\n        if ord(c) < 128:\n            result += c'}]
 ```
 
 Under the hood, the tokenizer [automatically splits by `<FILL_ME>`](https://huggingface.co/docs/transformers/main/model_doc/code_llama#transformers.CodeLlamaTokenizer.fill_token) to create a formatted input string that follows [the original training pattern](https://github.com/facebookresearch/codellama/blob/cb51c14ec761370ba2e2bc351374a79265d0465e/llama/generation.py#L402). This is more robust than preparing the pattern yourself: it avoids pitfalls, such as token glueing, that are very hard to debug.  To see how much CPU and GPU memory you need for this model or others, try [this calculator](https://huggingface.co/spaces/hf-accelerate/model-memory-usage) which can help determine that value.