[DOCS] Add example for `TopPLogitsWarper` (#25361)

* [DOCS] Add example for `TopPLogitsWarper`

* fix typo

* address review feedback

* address review nits

src/transformers/generation/logits_process.py

@@ -370,6 +370,37 @@ class TopPLogitsWarper(LogitsWarper):
             All filtered values will be set to this float value.
         min_tokens_to_keep (`int`, *optional*, defaults to 1):
             Minimum number of tokens that cannot be filtered.
+
+    Examples:
+    ```python
+    >>> from transformers import AutoTokenizer, AutoModelForCausalLM, set_seed
+
+    >>> set_seed(0)
+    >>> model = AutoModelForCausalLM.from_pretrained("gpt2")
+    >>> tokenizer = AutoTokenizer.from_pretrained("gpt2")
+
+    >>> text = "It is probably one of the most important things for parents to teach children about patience and acceptance. In this way, we as a society can ensure"
+    >>> inputs = tokenizer(text, return_tensors="pt")
+
+    >>> # Generate sequences without top_p sampling
+    >>> # We see that the answer tends to have a lot of repeated tokens and phrases
+    >>> outputs = model.generate(**inputs, max_length=55)
+    >>> print(tokenizer.batch_decode(outputs, skip_special_tokens=True)[0])
+    'It is probably one of the most important things for parents to teach children about patience and acceptance. In this way, we as a society can ensure that our children are not taught to be impatient or to be afraid of the future.\n\nThe first step is to teach them'
+
+    >>> # Generate sequences with top_p sampling: set `do_sample=True` to use top_p sampling with `top_p` arugment
+    >>> # We already see that the answer has less repetitive tokens and is more diverse
+    >>> outputs = model.generate(**inputs, max_length=55, do_sample=True, top_p=0.25)
+    >>> print(tokenizer.batch_decode(outputs, skip_special_tokens=True)[0])
+    'It is probably one of the most important things for parents to teach children about patience and acceptance. In this way, we as a society can ensure that children learn to be more accepting of others and to be more tolerant of others.\n\nWe can also teach children to be'
+
+    >>> # Generate sequences with top_p sampling with a larger top_p value
+    >>> # We see that as we increase the top_p value, less probable tokens also get selected during text generation, making the answer more diverse
+    >>> # Pro Tip: In practice, we tend to use top_p values between 0.9 and 1.0!
+    >>> outputs = model.generate(**inputs, max_length=55, do_sample=True, top_p=0.95)
+    >>> print(tokenizer.batch_decode(outputs, skip_special_tokens=True)[0])
+    'It is probably one of the most important things for parents to teach children about patience and acceptance. In this way, we as a society can ensure we have the best learning environment, so that we can teach to learn and not just take advantage of the environment.\n\nThe'
+    ```
     """
 
     def __init__(self, top_p: float, filter_value: float = -float("Inf"), min_tokens_to_keep: int = 1):