tiny fix

.dockerignore

@@ -4,10 +4,11 @@
 .venv
 cache
 data
+docker
+examples
+saves
 hf_cache
 output
-examples
 .dockerignore
 .gitattributes
 .gitignore
-Dockerfile

README.md

@@ -360,7 +360,7 @@ To enable FlashAttention-2 on the Windows platform, you need to install the prec
 
 <details><summary>For Ascend NPU users</summary>
 
-To install LLaMA Factory on Ascend NPU devices, please specify extra dependencies: `pip install -e '.[torch-npu,metrics]'`. Additionally, you need to install the **[Ascend CANN Toolkit and Kernels](https://www.hiascend.com/developer/download/community/result?module=cann)**. Please follow the [installation tutorial](https://www.hiascend.com/document/detail/en/CANNCommunityEdition/600alphaX/softwareinstall/instg/atlasdeploy_03_0031.html) or use the following commands:
+To install LLaMA Factory on Ascend NPU devices, please specify extra dependencies: `pip install -e ".[torch-npu,metrics]"`. Additionally, you need to install the **[Ascend CANN Toolkit and Kernels](https://www.hiascend.com/developer/download/community/result?module=cann)**. Please follow the [installation tutorial](https://www.hiascend.com/document/detail/en/CANNCommunityEdition/600alphaX/softwareinstall/instg/atlasdeploy_03_0031.html) or use the following commands:
 
 ```bash
 # replace the url according to your CANN version and devices
@@ -422,14 +422,16 @@ llamafactory-cli webui
 For CUDA users:
 
 ```bash
-docker-compose -f ./docker/docker-cuda/docker-compose.yml up -d
+cd docker/docker-cuda/
+docker-compose up -d
 docker-compose exec llamafactory bash
 ```
 
 For Ascend NPU users:
 
 ```bash
-docker-compose -f ./docker/docker-npu/docker-compose.yml up -d
+cd docker/docker-npu/
+docker-compose up -d
 docker-compose exec llamafactory bash
 ```
 
@@ -461,7 +463,7 @@ docker exec -it llamafactory bash
 For Ascend NPU users:
 
 ```bash
-# Change docker image upon your environment
+# Choose docker image upon your environment
 docker build -f ./docker/docker-npu/Dockerfile \
     --build-arg INSTALL_DEEPSPEED=false \
     --build-arg PIP_INDEX=https://pypi.org/simple \

README_zh.md

@@ -422,14 +422,16 @@ llamafactory-cli webui
 CUDA 用户：
 
 ```bash
-docker-compose -f ./docker/docker-cuda/docker-compose.yml up -d
+cd docker/docker-cuda/
+docker-compose up -d
 docker-compose exec llamafactory bash
 ```
 
 昇腾 NPU 用户：
 
 ```bash
-docker-compose -f ./docker/docker-npu/docker-compose.yml up -d
+cd docker/docker-npu/
+docker-compose up -d
 docker-compose exec llamafactory bash
 ```
 

src/llamafactory/data/formatter.py

@@ -216,7 +216,7 @@ class ToolFormatter(Formatter):
             self._tool_formatter = glm4_tool_formatter
             self._tool_extractor = glm4_tool_extractor
         else:
-            raise ValueError("Tool format was not found.")
+            raise NotImplementedError("Tool format {} was not found.".format(self.tool_format))
 
     def apply(self, **kwargs) -> SLOTS:
         content = kwargs.pop("content")

src/llamafactory/data/template.py

@@ -388,7 +388,8 @@ def get_template_and_fix_tokenizer(
         if template is None:
             raise ValueError("Template {} does not exist.".format(name))
 
-    if tool_format:
+    if tool_format is not None:
+        logger.info("Using tool format: {}.".format(tool_format))
         template.format_tools = ToolFormatter(tool_format=tool_format)
 
     stop_words = template.stop_words
@@ -625,7 +626,6 @@ _register_template(
 
 _register_template(
     name="empty",
-    format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
     efficient_eos=True,
 )
 

src/llamafactory/hparams/data_args.py

@@ -29,10 +29,6 @@ class DataArguments:
         default=None,
         metadata={"help": "Which template to use for constructing prompts in training and inference."},
     )
-    tool_format: Optional[str] = field(
-        default=None,
-        metadata={"help": "Specifies the tool format template for function calling ."},
-    )
     dataset: Optional[str] = field(
         default=None,
         metadata={"help": "The name of provided dataset(s) to use. Use commas to separate multiple datasets."},
@@ -105,6 +101,10 @@ class DataArguments:
             "help": "Whether or not to pack the sequences in training. Will automatically enable in pre-training."
         },
     )
+    tool_format: Optional[str] = field(
+        default=None,
+        metadata={"help": "Tool format to use for constructing function calling examples."},
+    )
     tokenized_path: Optional[str] = field(
         default=None,
         metadata={"help": "Path to save or load the tokenized datasets."},

src/llamafactory/webui/components/train.py

@@ -291,7 +291,7 @@ def create_train_tab(engine: "Engine") -> Dict[str, "Component"]:
         with gr.Column(scale=1):
             loss_viewer = gr.Plot()
 
-    input_elems.update({output_dir, config_path, device_count, ds_stage, ds_offload})
+    input_elems.update({output_dir, config_path, ds_stage, ds_offload})
     elem_dict.update(
         dict(
             cmd_preview_btn=cmd_preview_btn,

src/llamafactory/webui/runner.py

@@ -306,7 +306,7 @@ class Runner:
 
     def _form_config_dict(self, data: Dict["Component", Any]) -> Dict[str, Any]:
         config_dict = {}
-        skip_ids = ["top.lang", "top.model_path", "train.output_dir", "train.config_path", "train.device_count"]
+        skip_ids = ["top.lang", "top.model_path", "train.output_dir", "train.config_path"]
         for elem, value in data.items():
             elem_id = self.manager.get_id_by_elem(elem)
             if elem_id not in skip_ids: