Generate: All logits processors are documented and have examples (#27796)

Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

docs/source/en/llm_tutorial.md

@@ -250,7 +250,7 @@ While the autoregressive generation process is relatively straightforward, makin
 1. [Guide](generation_strategies) on how to control different generation methods, how to set up the generation configuration file, and how to stream the output;
 2. [Guide](chat_templating) on the prompt template for chat LLMs;
 3. [Guide](tasks/prompting) on to get the most of prompt design;
-4. API reference on [`~generation.GenerationConfig`], [`~generation.GenerationMixin.generate`], and [generate-related classes](internal/generation_utils).
+4. API reference on [`~generation.GenerationConfig`], [`~generation.GenerationMixin.generate`], and [generate-related classes](internal/generation_utils). Most of the classes, including the logits processors, have usage examples!
 
 ### LLM leaderboards
 

src/transformers/generation/configuration_utils.py

@@ -63,6 +63,14 @@ class GenerationConfig(PushToHubMixin):
     You do not need to call any of the above methods directly. Pass custom parameter values to '.generate()'. To learn
     more about decoding strategies refer to the [text generation strategies guide](../generation_strategies).
 
+    <Tip>
+
+    A large number of these flags control the logits or the stopping criteria of the generation. Make sure you check
+    the [generate-related classes](https://huggingface.co/docs/transformers/internal/generation_utils) for a full
+    description of the possible manipulations, as well as examples of their usage.
+
+    </Tip>
+
     Arg:
         > Parameters that control the length of the output
 

src/transformers/generation/utils.py

@@ -1031,15 +1031,8 @@ class GenerationMixin:
             generation_config.encoder_no_repeat_ngram_size is not None
             and generation_config.encoder_no_repeat_ngram_size > 0
         ):
-            if self.config.is_encoder_decoder:
             processors.append(
-                    EncoderNoRepeatNGramLogitsProcessor(
-                        generation_config.encoder_no_repeat_ngram_size, encoder_input_ids
-                    )
-                )
-            else:
-                raise ValueError(
-                    "It's impossible to use `encoder_no_repeat_ngram_size` with decoder-only architecture"
+                EncoderNoRepeatNGramLogitsProcessor(generation_config.encoder_no_repeat_ngram_size, encoder_input_ids)
             )
         if generation_config.bad_words_ids is not None:
             processors.append(