add llava to llamaboard

examples/inference/web_demo.sh

@@ -1,4 +1,5 @@
 #!/bin/bash
+# add `--visual_inputs True` to load MLLM
 
 CUDA_VISIBLE_DEVICES=0 python ../../src/web_demo.py \
     --model_name_or_path meta-llama/Llama-2-7b-hf \

src/llmtuner/extras/constants.py

@@ -28,6 +28,8 @@
 
 METHODS = ["full", "freeze", "lora"]
 
+MLLM_LIST = ["LLaVA1.5"]
+
 MOD_SUPPORTED_MODELS = ["bloom", "falcon", "gemma", "llama", "mistral", "mixtral", "phi", "starcoder2"]
 
 PEFT_METHODS = ["lora"]
@@ -566,6 +568,19 @@ def register_model_group(
 )
 
 
+register_model_group(
+    models={
+        "LLaVA1.5-7B-Chat": {
+            DownloadSource.DEFAULT: "llava-hf/llava-1.5-7b-hf",
+        },
+        "LLaVA1.5-13B-Chat": {
+            DownloadSource.DEFAULT: "llava-hf/llava-1.5-13b-hf",
+        },
+    },
+    template="vicuna",
+)
+
+
 register_model_group(
     models={
         "Mistral-7B-v0.1": {

src/llmtuner/webui/chatter.py

@@ -79,6 +79,7 @@ def load_model(self, data) -> Generator[str, None, None]:
             template=get("top.template"),
             flash_attn="fa2" if get("top.booster") == "flashattn2" else "auto",
             use_unsloth=(get("top.booster") == "unsloth"),
+            visual_inputs=get("top.visual_inputs"),
             rope_scaling=get("top.rope_scaling") if get("top.rope_scaling") in ["linear", "dynamic"] else None,
             infer_backend=get("infer.infer_backend"),
         )

src/llmtuner/webui/common.py

@@ -9,6 +9,7 @@
     DATA_CONFIG,
     DEFAULT_MODULE,
     DEFAULT_TEMPLATE,
+    MLLM_LIST,
     PEFT_METHODS,
     STAGES_USE_PAIR_DATA,
     SUPPORTED_MODELS,
@@ -105,6 +106,10 @@ def get_template(model_name: str) -> str:
     return "default"
 
 
+def get_visual(model_name: str) -> bool:
+    return get_prefix(model_name) in MLLM_LIST
+
+
 def list_adapters(model_name: str, finetuning_type: str) -> "gr.Dropdown":
     if finetuning_type not in PEFT_METHODS:
         return gr.Dropdown(value=[], choices=[], interactive=False)

src/llmtuner/webui/components/chatbot.py

@@ -17,7 +17,7 @@
 
 def create_chat_box(
     engine: "Engine", visible: bool = False
-) -> Tuple["gr.Column", "Component", "Component", Dict[str, "Component"]]:
+) -> Tuple["Component", "Component", Dict[str, "Component"]]:
     with gr.Column(visible=visible) as chat_box:
         chatbot = gr.Chatbot(show_copy_button=True)
         messages = gr.State([])
@@ -29,7 +29,7 @@ def create_chat_box(
                         system = gr.Textbox(show_label=False)
                         tools = gr.Textbox(show_label=False, lines=4)
 
-                    with gr.Column():
+                    with gr.Column() as image_box:
                         image = gr.Image(type="numpy")
 
                 query = gr.Textbox(show_label=False, lines=8)
@@ -55,13 +55,14 @@ def create_chat_box(
     clear_btn.click(lambda: ([], []), outputs=[chatbot, messages])
 
     return (
-        chat_box,
         chatbot,
         messages,
         dict(
+            chat_box=chat_box,
             role=role,
             system=system,
             tools=tools,
+            image_box=image_box,
             image=image,
             query=query,
             submit_btn=submit_btn,

src/llmtuner/webui/components/export.py

@@ -27,6 +27,7 @@ def save_model(
     adapter_path: List[str],
     finetuning_type: str,
     template: str,
+    visual_inputs: bool,
     export_size: int,
     export_quantization_bit: int,
     export_quantization_dataset: str,
@@ -66,6 +67,7 @@ def save_model(
         adapter_name_or_path=adapter_name_or_path,
         finetuning_type=finetuning_type,
         template=template,
+        visual_inputs=visual_inputs,
         export_dir=export_dir,
         export_hub_model_id=export_hub_model_id or None,
         export_size=export_size,
@@ -105,6 +107,7 @@ def create_export_tab(engine: "Engine") -> Dict[str, "Component"]:
             engine.manager.get_elem_by_id("top.adapter_path"),
             engine.manager.get_elem_by_id("top.finetuning_type"),
             engine.manager.get_elem_by_id("top.template"),
+            engine.manager.get_elem_by_id("top.visual_inputs"),
             export_size,
             export_quantization_bit,
             export_quantization_dataset,

src/llmtuner/webui/components/infer.py

@@ -28,15 +28,21 @@ def create_infer_tab(engine: "Engine") -> Dict[str, "Component"]:
     input_elems.update({infer_backend})
     elem_dict.update(dict(infer_backend=infer_backend, load_btn=load_btn, unload_btn=unload_btn, info_box=info_box))
 
-    chat_box, chatbot, messages, chat_elems = create_chat_box(engine, visible=False)
-    elem_dict.update(dict(chat_box=chat_box, **chat_elems))
+    chatbot, messages, chat_elems = create_chat_box(engine, visible=False)
+    elem_dict.update(chat_elems)
 
     load_btn.click(engine.chatter.load_model, input_elems, [info_box]).then(
-        lambda: gr.Column(visible=engine.chatter.loaded), outputs=[chat_box]
+        lambda: gr.Column(visible=engine.chatter.loaded), outputs=[chat_elems["chat_box"]]
     )
 
     unload_btn.click(engine.chatter.unload_model, input_elems, [info_box]).then(
         lambda: ([], []), outputs=[chatbot, messages]
-    ).then(lambda: gr.Column(visible=engine.chatter.loaded), outputs=[chat_box])
+    ).then(lambda: gr.Column(visible=engine.chatter.loaded), outputs=[chat_elems["chat_box"]])
+
+    engine.manager.get_elem_by_id("top.visual_inputs").change(
+        lambda enabled: gr.Column(visible=enabled),
+        [engine.manager.get_elem_by_id("top.visual_inputs")],
+        [chat_elems["image_box"]],
+    )
 
     return elem_dict

src/llmtuner/webui/components/top.py

@@ -3,7 +3,7 @@
 from ...data import templates
 from ...extras.constants import METHODS, SUPPORTED_MODELS
 from ...extras.packages import is_gradio_available
-from ..common import get_model_path, get_template, list_adapters, save_config
+from ..common import get_model_path, get_template, get_visual, list_adapters, save_config
 from ..utils import can_quantize
 
 
@@ -30,14 +30,17 @@ def create_top() -> Dict[str, "Component"]:
 
     with gr.Accordion(open=False) as advanced_tab:
         with gr.Row():
-            quantization_bit = gr.Dropdown(choices=["none", "8", "4"], value="none")
-            template = gr.Dropdown(choices=list(templates.keys()), value="default")
-            rope_scaling = gr.Radio(choices=["none", "linear", "dynamic"], value="none")
-            booster = gr.Radio(choices=["none", "flashattn2", "unsloth"], value="none")
+            quantization_bit = gr.Dropdown(choices=["none", "8", "4"], value="none", scale=2)
+            template = gr.Dropdown(choices=list(templates.keys()), value="default", scale=2)
+            rope_scaling = gr.Radio(choices=["none", "linear", "dynamic"], value="none", scale=3)
+            booster = gr.Radio(choices=["none", "flashattn2", "unsloth"], value="none", scale=3)
+            visual_inputs = gr.Checkbox(scale=1)
 
     model_name.change(list_adapters, [model_name, finetuning_type], [adapter_path], queue=False).then(
         get_model_path, [model_name], [model_path], queue=False
-    ).then(get_template, [model_name], [template], queue=False)  # do not save config since the below line will save
+    ).then(get_template, [model_name], [template], queue=False).then(
+        get_visual, [model_name], [visual_inputs], queue=False
+    )  # do not save config since the below line will save
 
     model_path.change(save_config, inputs=[lang, model_name, model_path], queue=False)
 
@@ -59,4 +62,5 @@ def create_top() -> Dict[str, "Component"]:
         template=template,
         rope_scaling=rope_scaling,
         booster=booster,
+        visual_inputs=visual_inputs,
     )

src/llmtuner/webui/engine.py

@@ -43,6 +43,7 @@ def resume(self):
             init_dict["train.output_dir"] = {"value": "train_{}".format(get_time())}
             init_dict["train.config_path"] = {"value": "{}.json".format(get_time())}
             init_dict["eval.output_dir"] = {"value": "eval_{}".format(get_time())}
+            init_dict["infer.image_box"] = {"visible": False}
 
             if user_config.get("last_model", None):
                 init_dict["top.model_name"] = {"value": user_config["last_model"]}

src/llmtuner/webui/interface.py

@@ -58,8 +58,8 @@ def create_web_demo() -> gr.Blocks:
         lang = gr.Dropdown(choices=["en", "zh"])
         engine.manager.add_elems("top", dict(lang=lang))
 
-        chat_box, _, _, chat_elems = create_chat_box(engine, visible=True)
-        engine.manager.add_elems("infer", dict(chat_box=chat_box, **chat_elems))
+        _, _, chat_elems = create_chat_box(engine, visible=True)
+        engine.manager.add_elems("infer", chat_elems)
 
         demo.load(engine.resume, outputs=engine.manager.get_elem_list(), concurrency_limit=None)
         lang.change(engine.change_lang, [lang], engine.manager.get_elem_list(), queue=False)

src/llmtuner/webui/locales.py

@@ -129,6 +129,17 @@
             "label": "加速方式",
         },
     },
+    "visual_inputs": {
+        "en": {
+            "label": "Visual inputs",
+        },
+        "ru": {
+            "label": "визуальные входы",
+        },
+        "zh": {
+            "label": "图像输入",
+        },
+    },
     "training_stage": {
         "en": {
             "label": "Stage",

src/llmtuner/webui/manager.py

@@ -60,4 +60,5 @@ def get_base_elems(self) -> Set["Component"]:
             self._id_to_elem["top.template"],
             self._id_to_elem["top.rope_scaling"],
             self._id_to_elem["top.booster"],
+            self._id_to_elem["top.visual_inputs"],
         }

src/llmtuner/webui/runner.py

@@ -124,6 +124,7 @@ def _parse_train_args(self, data: Dict["Component", Any]) -> Dict[str, Any]:
             rope_scaling=get("top.rope_scaling") if get("top.rope_scaling") in ["linear", "dynamic"] else None,
             flash_attn="fa2" if get("top.booster") == "flashattn2" else "auto",
             use_unsloth=(get("top.booster") == "unsloth"),
+            visual_inputs=get("top.visual_inputs"),
             dataset_dir=get("train.dataset_dir"),
             dataset=",".join(get("train.dataset")),
             cutoff_len=get("train.cutoff_len"),
@@ -224,6 +225,7 @@ def _parse_eval_args(self, data: Dict["Component", Any]) -> Dict[str, Any]:
             rope_scaling=get("top.rope_scaling") if get("top.rope_scaling") in ["linear", "dynamic"] else None,
             flash_attn="fa2" if get("top.booster") == "flashattn2" else "auto",
             use_unsloth=(get("top.booster") == "unsloth"),
+            visual_inputs=get("top.visual_inputs"),
             dataset_dir=get("eval.dataset_dir"),
             dataset=",".join(get("eval.dataset")),
             cutoff_len=get("eval.cutoff_len"),