Retrieve license information when local files are provided for a pret…

…rained model (#943)

* Initial implementation to test

* Add log for license overwrite

* Use Path for input to _write_license_information

* Set default

---------

Co-authored-by: Daniel King <[email protected]>

llmfoundry/callbacks/hf_checkpointer.py

@@ -20,6 +20,7 @@
                             maybe_create_remote_uploader_downloader_from_uri,
                             parse_uri)
 from composer.utils.misc import create_interval_scheduler
+from mlflow.transformers import _fetch_model_card, _write_license_information
 from transformers import PreTrainedModel, PreTrainedTokenizerBase
 
 from llmfoundry.models.mpt import MPTConfig, MPTForCausalLM
@@ -32,17 +33,41 @@
 _LICENSE_FILE_PATTERN = re.compile(r'license(\.[a-z]+|$)', re.IGNORECASE)
 
 
-def _maybe_get_license_filename(local_dir: str) -> Optional[str]:
+def _maybe_get_license_filename(
+        local_dir: str,
+        pretrained_model_name: Optional[str] = None) -> Optional[str]:
     """Returns the name of the license file if it exists in the local_dir.
 
     Note: This is intended to be consistent with the code in MLflow.
     https://github.com/mlflow/mlflow/blob/5d13d6ec620a02de9a5e31201bf1becdb9722ea5/mlflow/transformers/__init__.py#L1152
 
+    Since LLM Foundry supports local model files being used rather than fetching the files from the Hugging Face Hub,
+    MLflow's logic to fetch and write the license information on model save is not applicable; it will try to search for
+    a Hugging Face repo named after the local path. However, the user can provide the original pretrained model name,
+    in which case this function will use that to fetch the correct license information.
+
     If the license file does not exist, returns None.
     """
     try:
-        return next(file for file in os.listdir(local_dir)
-                    if _LICENSE_FILE_PATTERN.search(file))
+        license_filename = next(file for file in os.listdir(local_dir)
+                                if _LICENSE_FILE_PATTERN.search(file))
+
+        # If a pretrained model name is provided, replace the license file with the correct info from HF Hub.
+        if pretrained_model_name is not None:
+            log.info(
+                f'Overwriting license file {license_filename} with license info for model {pretrained_model_name} from Hugging Face Hub'
+            )
+            os.remove(os.path.join(local_dir, license_filename))
+            model_card = _fetch_model_card(pretrained_model_name)
+
+            local_dir_path = Path(local_dir).absolute()
+            _write_license_information(pretrained_model_name, model_card,
+                                       local_dir_path)
+            license_filename = next(file for file in os.listdir(local_dir)
+                                    if _LICENSE_FILE_PATTERN.search(file))
+
+        return license_filename
+
     except StopIteration:
         return None
 
@@ -330,8 +355,11 @@ def _save_checkpoint(self, state: State, logger: Logger):
 
                         mlflow_logger.save_model(**model_saving_kwargs)
 
+                        # Upload the license file generated by mlflow during the model saving.
                         license_filename = _maybe_get_license_filename(
-                            local_save_path)
+                            local_save_path,
+                            self.mlflow_logging_config['metadata'].get(
+                                'pretrained_model_name', None))
                         if license_filename is not None:
                             mlflow_logger._mlflow_client.log_artifact(
                                 mlflow_logger._run_id,