[generate] Run custom generation code from the Hub (#36405)

* mvp

* remove trust_remote_code

* generate_from_hub

* handle requirements; docs

* english

* doc PR suggestions

* Apply suggestions from code review

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* changed remote code path to generate/generate.py

* model repo has custom generate -> override base generate

* check for proper inheritance

* some doc updates (missing: tag-related docs)

* update docs to model repo

* nit

* nit

* nits

* Update src/transformers/dynamic_module_utils.py

* Apply suggestions from code review

* Update docs/source/en/generation_strategies.md

Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* trust remote code is required

* use new import utils for requirements version parsing

* use  org examples

* add tests

* Apply suggestions from code review

Co-authored-by: Manuel de Prada Corral <6536835+manueldeprada@users.noreply.github.com>

* ascii file structure; tag instructions on readme.md

---------

Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Manuel de Prada Corral <6536835+manueldeprada@users.noreply.github.com>

src/transformers/modeling_utils.py

@@ -4104,6 +4104,7 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, PushToHubMixin, PeftAdapterMi
         gguf_file = kwargs.pop("gguf_file", None)
         tp_plan = kwargs.pop("tp_plan", None)
         tp_size = kwargs.pop("tp_size", None)
+        trust_remote_code = kwargs.pop("trust_remote_code", None)
 
         # Load models with hardcoded key mapping on class for VLMs only,  to keep BC and standardize model
         if any(allowed_name in cls.__name__.lower() for allowed_name in VLMS):
@@ -4113,7 +4114,6 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, PushToHubMixin, PeftAdapterMi
 
         # Not used anymore -- remove them from the kwargs
         _ = kwargs.pop("resume_download", None)
-        _ = kwargs.pop("trust_remote_code", None)
         _ = kwargs.pop("mirror", None)
         _ = kwargs.pop("_fast_init", True)
         _ = kwargs.pop("low_cpu_mem_usage", None)
@@ -4591,30 +4591,44 @@ class PreTrainedModel(nn.Module, ModuleUtilsMixin, PushToHubMixin, PeftAdapterMi
         # Set model in evaluation mode to deactivate DropOut modules by default
         model.eval()
 
-        # If it is a model with generation capabilities, attempt to load the generation config
+        # If it is a model with generation capabilities, attempt to load generation files (generation config,
+        # custom generate function)
         if model.can_generate() and generation_config is not None:
             logger.info("The user-defined `generation_config` will be used to override the default generation config.")
             model.generation_config = model.generation_config.from_dict(generation_config.to_dict())
         elif model.can_generate() and pretrained_model_name_or_path is not None:
+            repo_loading_kwargs = {
+                "cache_dir": cache_dir,
+                "force_download": force_download,
+                "proxies": proxies,
+                "local_files_only": local_files_only,
+                "token": token,
+                "revision": revision,
+                "subfolder": subfolder,
+                **kwargs,
+            }
+            # Load generation config
             try:
                 model.generation_config = GenerationConfig.from_pretrained(
                     pretrained_model_name_or_path,
-                    cache_dir=cache_dir,
-                    force_download=force_download,
-                    proxies=proxies,
-                    local_files_only=local_files_only,
-                    token=token,
-                    revision=revision,
-                    subfolder=subfolder,
                     _from_auto=from_auto_class,
                     _from_pipeline=from_pipeline,
-                    **kwargs,
+                    **repo_loading_kwargs,
                 )
             except OSError:
                 logger.info(
                     "Generation config file not found, using a generation config created from the model config."
                 )
                 pass
+            # Load custom generate function if `pretrained_model_name_or_path` defines it (and override `generate`)
+            if hasattr(model, "load_custom_generate"):
+                try:
+                    custom_generate = model.load_custom_generate(
+                        pretrained_model_name_or_path, trust_remote_code=trust_remote_code, **repo_loading_kwargs
+                    )
+                    model.generate = functools.partial(custom_generate, model=model)
+                except OSError:  # there is no custom generate function
+                    pass
 
         # Dispatch model with hooks on all devices if necessary (not needed with a tp_plan, so we skip it as it slightly
         # harm performances)