Support llama3.2vl.

Former-commit-id: 3f2c056253c651e8e614c787e2045f4232e82666

src/llamafactory/data/mm_plugin.py

@@ -4,6 +4,7 @@ from io import BytesIO
 from typing import TYPE_CHECKING, Dict, List, Optional, Sequence, Tuple, TypedDict, Union
 
 import numpy as np
+import torch
 from transformers.image_utils import get_image_size, to_numpy_array
 from typing_extensions import override
 
@@ -21,7 +22,6 @@ if is_pyav_available():
 
 
 if TYPE_CHECKING:
-    import torch
     from av.stream import Stream
     from transformers import PreTrainedTokenizer, ProcessorMixin
     from transformers.image_processing_utils import BaseImageProcessor
@@ -676,6 +676,49 @@ class VideoLlavaPlugin(BasePlugin):
         return self._get_mm_inputs(images, videos, processor)
 
 
+class MllamaPlugin(BasePlugin):
+    @override
+    def process_messages(
+        self,
+        messages: Sequence[Dict[str, str]],
+        images: Sequence["ImageInput"],
+        videos: Sequence["VideoInput"],
+        processor: Optional["ProcessorMixin"],
+    ) -> List[Dict[str, str]]:
+        self._validate_input(images, videos)
+        num_image_tokens = 0
+        messages = deepcopy(messages)
+        for message in messages:
+            content = message["content"]
+            while IMAGE_PLACEHOLDER in content:
+                num_image_tokens += 1
+                content = content.replace(IMAGE_PLACEHOLDER, "<|image|>", 1)
+
+            message["content"] = content
+
+        if len(images) != num_image_tokens:
+            raise ValueError("The number of images does not match the number of {} tokens".format(IMAGE_PLACEHOLDER))
+
+        return messages
+
+    def get_mm_inputs(
+        self,
+        images: Sequence["ImageInput"],
+        videos: Sequence["VideoInput"],
+        imglens: Sequence[int],
+        vidlens: Sequence[int],
+        seqlens: Sequence[int],
+        processor: Optional["ProcessorMixin"],
+    ) -> Dict[str, Union[List[int], "torch.Tensor"]]:
+        super().get_mm_inputs(images, videos, imglens, vidlens, seqlens, processor)
+        if images is not None:
+            images = [Image.open(image) if isinstance(image, str) else image for image in images]
+            image_features = processor.image_processor(images)
+            _ = image_features.pop("num_tiles")
+        image_features = {k: v if isinstance(v, torch.Tensor) else torch.tensor(v) for k, v in image_features.items()}
+        return image_features
+
+
 PLUGINS = {
     "base": BasePlugin,
     "llava": LlavaPlugin,
@@ -685,6 +728,7 @@ PLUGINS = {
     "pixtral": PixtralPlugin,
     "qwen2_vl": Qwen2vlPlugin,
     "video_llava": VideoLlavaPlugin,
+    "mllama": MllamaPlugin,
 }
 
 

src/llamafactory/data/template.py

@@ -762,6 +762,33 @@ _register_template(
 )
 
 
+_register_template(
+    name="mllama",
+    format_user=StringFormatter(
+        slots=[
+            (
+                "<|start_header_id|>user<|end_header_id|>\n\n{{content}}<|eot_id|>"
+                "<|start_header_id|>assistant<|end_header_id|>\n\n"
+            )
+        ]
+    ),
+    format_system=StringFormatter(slots=["<|start_header_id|>system<|end_header_id|>\n\n{{content}}<|eot_id|>"]),
+    format_observation=StringFormatter(
+        slots=[
+            (
+                "<|start_header_id|>tool<|end_header_id|>\n\n{{content}}<|eot_id|>"
+                "<|start_header_id|>assistant<|end_header_id|>\n\n"
+            )
+        ]
+    ),
+    format_prefix=EmptyFormatter(slots=[{"bos_token"}]),
+    stop_words=["<|eot_id|>"],
+    replace_eos=True,
+    replace_jinja_template=False,
+    mm_plugin=get_mm_plugin(name="mllama", image_token="<image>"),
+)
+
+
 _register_template(
     name="llava",
     format_user=StringFormatter(slots=["USER: {{content}} ASSISTANT:"]),

src/llamafactory/extras/constants.py

@@ -855,6 +855,22 @@ register_model_group(
 )
 
 
+register_model_group(
+    models={
+        "Llama-3.2-11B-Vision-Instruct": {
+            DownloadSource.DEFAULT: "meta-llama/Llama-3.2-11B-Vision-Instruct",
+            DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-11B-Vision-Instruct",
+        },
+        "LlamaVision3.2-90B-Instruct": {
+            DownloadSource.DEFAULT: "meta-llama/Llama-3.2-90B-Vision-Instruct",
+            DownloadSource.MODELSCOPE: "LLM-Research/Llama-3.2-90B-Vision-Instruct",
+        },
+    },
+    template="mllama",
+    vision=True,
+)
+
+
 register_model_group(
     models={
         "LLaVA-1.5-7B-Chat": {