support llama pro #2338 , add rslora

Former-commit-id: 40d659b7f30dd5a004703c176ec1f22dc864e505

src/llmtuner/train/utils.py

@@ -4,7 +4,7 @@ import torch
 
 from ..extras.logging import get_logger
 from ..hparams import FinetuningArguments, ModelArguments
-from ..model import get_modelcard_args, load_model_and_tokenizer, load_valuehead_params
+from ..model import load_model_and_tokenizer, load_valuehead_params
 
 
 if TYPE_CHECKING:
@@ -25,14 +25,18 @@ def create_modelcard_and_push(
     training_args: "Seq2SeqTrainingArguments",
     finetuning_args: "FinetuningArguments",
 ) -> None:
-    if training_args.do_train:
-        if training_args.push_to_hub:
-            trainer.push_to_hub(**get_modelcard_args(model_args, data_args, finetuning_args))
-            return
-        try:
-            trainer.create_model_card(**get_modelcard_args(model_args, data_args, finetuning_args))
-        except Exception as err:
-            logger.warning("Failed to create model card: {}".format(str(err)))
+    kwargs = {
+        "tasks": "text-generation",
+        "finetuned_from": model_args.model_name_or_path,
+        "dataset": [dataset.strip() for dataset in data_args.dataset.split(",")],
+        "tags": ["llama-factory", finetuning_args.finetuning_type],
+    }
+    if not training_args.do_train:
+        pass
+    elif training_args.push_to_hub:
+        trainer.push_to_hub(**kwargs)
+    else:
+        trainer.create_model_card(license="other", **kwargs)  # prevent from connecting to hub
 
 
 def create_ref_model(