From b40f266617e82ee9a1ec7dc0475808feeacd96b0 Mon Sep 17 00:00:00 2001
From: hiyouga <hiyouga@buaa.edu.cn>
Date: Tue, 16 Apr 2024 00:25:03 +0800
Subject: [PATCH] support unsloth 2024.4

Former-commit-id: 7dc72fb58cb988418323f63821a21a184ecf0718
---
 src/llmtuner/model/adapter.py | 8 ++++++--
 src/llmtuner/model/loader.py  | 2 ++
 2 files changed, 8 insertions(+), 2 deletions(-)

diff --git a/src/llmtuner/model/adapter.py b/src/llmtuner/model/adapter.py
index 4bb4057d..cabb21df 100644
--- a/src/llmtuner/model/adapter.py
+++ b/src/llmtuner/model/adapter.py
@@ -145,18 +145,22 @@ def init_adapter(
                 "lora_alpha": finetuning_args.lora_alpha,
                 "lora_dropout": finetuning_args.lora_dropout,
                 "use_rslora": finetuning_args.use_rslora,
+                "modules_to_save": finetuning_args.additional_target,
             }
 
             if model_args.use_unsloth:
                 from unsloth import FastLanguageModel  # type: ignore
 
-                unsloth_peft_kwargs = {"model": model, "max_seq_length": model_args.model_max_length}
+                unsloth_peft_kwargs = {
+                    "model": model,
+                    "max_seq_length": model_args.model_max_length,
+                    "use_gradient_checkpointing": "unsloth",
+                }
                 model = FastLanguageModel.get_peft_model(**peft_kwargs, **unsloth_peft_kwargs)
             else:
                 lora_config = LoraConfig(
                     task_type=TaskType.CAUSAL_LM,
                     inference_mode=False,
-                    modules_to_save=finetuning_args.additional_target,
                     use_dora=finetuning_args.use_dora,
                     **peft_kwargs,
                 )
diff --git a/src/llmtuner/model/loader.py b/src/llmtuner/model/loader.py
index aeb22850..7ab8222f 100644
--- a/src/llmtuner/model/loader.py
+++ b/src/llmtuner/model/loader.py
@@ -82,6 +82,8 @@ def load_model(
             "token": model_args.hf_hub_token,
             "device_map": {"": get_current_device()},
             "rope_scaling": getattr(config, "rope_scaling", None),
+            "fix_tokenizer": False,
+            "trust_remote_code": True,
         }
         try:
             model, _ = FastLanguageModel.from_pretrained(**unsloth_kwargs)