Generate: generation config validation fixes in docs (#25405)

docs/source/en/model_doc/donut.md

@@ -80,11 +80,9 @@ into a single instance to both extract the input features and decode the predict
 ...     pixel_values.to(device),
 ...     decoder_input_ids=decoder_input_ids.to(device),
 ...     max_length=model.decoder.config.max_position_embeddings,
-...     early_stopping=True,
 ...     pad_token_id=processor.tokenizer.pad_token_id,
 ...     eos_token_id=processor.tokenizer.eos_token_id,
 ...     use_cache=True,
-...     num_beams=1,
 ...     bad_words_ids=[[processor.tokenizer.unk_token_id]],
 ...     return_dict_in_generate=True,
 ... )
@@ -125,11 +123,9 @@ into a single instance to both extract the input features and decode the predict
 ...     pixel_values.to(device),
 ...     decoder_input_ids=decoder_input_ids.to(device),
 ...     max_length=model.decoder.config.max_position_embeddings,
-...     early_stopping=True,
 ...     pad_token_id=processor.tokenizer.pad_token_id,
 ...     eos_token_id=processor.tokenizer.eos_token_id,
 ...     use_cache=True,
-...     num_beams=1,
 ...     bad_words_ids=[[processor.tokenizer.unk_token_id]],
 ...     return_dict_in_generate=True,
 ... )
@@ -172,11 +168,9 @@ into a single instance to both extract the input features and decode the predict
 ...     pixel_values.to(device),
 ...     decoder_input_ids=decoder_input_ids.to(device),
 ...     max_length=model.decoder.config.max_position_embeddings,
-...     early_stopping=True,
 ...     pad_token_id=processor.tokenizer.pad_token_id,
 ...     eos_token_id=processor.tokenizer.eos_token_id,
 ...     use_cache=True,
-...     num_beams=1,
 ...     bad_words_ids=[[processor.tokenizer.unk_token_id]],
 ...     return_dict_in_generate=True,
 ... )

src/transformers/generation/configuration_utils.py

@@ -597,7 +597,7 @@ class GenerationConfig(PushToHubMixin):
         >>> # If you'd like to try a minor variation to an existing configuration, you can also pass generation
         >>> # arguments to `.from_pretrained()`. Be mindful that typos and unused arguments will be ignored
         >>> generation_config, unused_kwargs = GenerationConfig.from_pretrained(
-        ...     "gpt2", top_k=1, foo=False, return_unused_kwargs=True
+        ...     "gpt2", top_k=1, foo=False, do_sample=True, return_unused_kwargs=True
         ... )
         >>> generation_config.top_k
         1