[model] support mistral 2506

docs/source/Instruction/Supported-models-and-datasets.md

@@ -1024,6 +1024,7 @@
 |[google/gemma-3n-E4B-it](https://modelscope.cn/models/google/gemma-3n-E4B-it)|gemma3n|gemma3n|transformers>=4.53.1|✘|-|[google/gemma-3n-E4B-it](https://huggingface.co/google/gemma-3n-E4B-it)|
 |[mistralai/Mistral-Small-3.1-24B-Base-2503](https://modelscope.cn/models/mistralai/Mistral-Small-3.1-24B-Base-2503)|mistral_2503|mistral_2503|transformers>=4.49|✘|-|[mistralai/Mistral-Small-3.1-24B-Base-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Base-2503)|
 |[mistralai/Mistral-Small-3.1-24B-Instruct-2503](https://modelscope.cn/models/mistralai/Mistral-Small-3.1-24B-Instruct-2503)|mistral_2503|mistral_2503|transformers>=4.49|✘|-|[mistralai/Mistral-Small-3.1-24B-Instruct-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503)|
+|[mistralai/Mistral-Small-3.2-24B-Instruct-2506](https://modelscope.cn/models/mistralai/Mistral-Small-3.2-24B-Instruct-2506)|mistral_2506|mistral_2506|transformers>=4.49|✘|-|[mistralai/Mistral-Small-3.2-24B-Instruct-2506](https://huggingface.co/mistralai/Mistral-Small-3.2-24B-Instruct-2506)|
 |[PaddlePaddle/PaddleOCR-VL](https://modelscope.cn/models/PaddlePaddle/PaddleOCR-VL)|paddle_ocr|paddle_ocr|-|✘|-|[PaddlePaddle/PaddleOCR-VL](https://huggingface.co/PaddlePaddle/PaddleOCR-VL)|
 |[JinaAI/jina-reranker-m0](https://modelscope.cn/models/JinaAI/jina-reranker-m0)|jina_reranker_m0|jina_reranker_m0|-|✘|reranker, vision|[JinaAI/jina-reranker-m0](https://huggingface.co/JinaAI/jina-reranker-m0)|
 

docs/source_en/Instruction/Supported-models-and-datasets.md

@@ -1024,6 +1024,7 @@ The table below introduces the models integrated with ms-swift:
 |[google/gemma-3n-E4B-it](https://modelscope.cn/models/google/gemma-3n-E4B-it)|gemma3n|gemma3n|transformers>=4.53.1|✘|-|[google/gemma-3n-E4B-it](https://huggingface.co/google/gemma-3n-E4B-it)|
 |[mistralai/Mistral-Small-3.1-24B-Base-2503](https://modelscope.cn/models/mistralai/Mistral-Small-3.1-24B-Base-2503)|mistral_2503|mistral_2503|transformers>=4.49|✘|-|[mistralai/Mistral-Small-3.1-24B-Base-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Base-2503)|
 |[mistralai/Mistral-Small-3.1-24B-Instruct-2503](https://modelscope.cn/models/mistralai/Mistral-Small-3.1-24B-Instruct-2503)|mistral_2503|mistral_2503|transformers>=4.49|✘|-|[mistralai/Mistral-Small-3.1-24B-Instruct-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503)|
+|[mistralai/Mistral-Small-3.2-24B-Instruct-2506](https://modelscope.cn/models/mistralai/Mistral-Small-3.2-24B-Instruct-2506)|mistral_2506|mistral_2506|transformers>=4.49|✘|-|[mistralai/Mistral-Small-3.2-24B-Instruct-2506](https://huggingface.co/mistralai/Mistral-Small-3.2-24B-Instruct-2506)|
 |[PaddlePaddle/PaddleOCR-VL](https://modelscope.cn/models/PaddlePaddle/PaddleOCR-VL)|paddle_ocr|paddle_ocr|-|✘|-|[PaddlePaddle/PaddleOCR-VL](https://huggingface.co/PaddlePaddle/PaddleOCR-VL)|
 |[JinaAI/jina-reranker-m0](https://modelscope.cn/models/JinaAI/jina-reranker-m0)|jina_reranker_m0|jina_reranker_m0|-|✘|reranker, vision|[JinaAI/jina-reranker-m0](https://huggingface.co/JinaAI/jina-reranker-m0)|
 

swift/llm/model/constant.py

@@ -274,6 +274,7 @@ class MLLMModelType:
     gemma3_vision = 'gemma3_vision'
     gemma3n = 'gemma3n'
     mistral_2503 = 'mistral_2503'
+    mistral_2506 = 'mistral_2506'
     paddle_ocr = 'paddle_ocr'
 
 

swift/llm/model/model/mistral.py

@@ -1,8 +1,7 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
-
 from typing import Any, Dict
 
-from transformers import AutoTokenizer
+from transformers import AutoProcessor, AutoTokenizer
 
 from swift.llm import TemplateType
 from ..constant import LLMModelType, MLLMModelType
@@ -130,12 +129,7 @@ def get_model_tokenizer_mistral_2503(model_dir: str,
                                      model_kwargs: Dict[str, Any],
                                      load_model: bool = True,
                                      **kwargs):
-    try:
-        from transformers import Mistral3ForConditionalGeneration
-    except ImportError:
-        raise ImportError('Please install Mistral3ForConditionalGeneration by running '
-                          '`pip install git+https://github.com/huggingface/transformers@v4.49.0-Mistral-3`')
-
+    from transformers import Mistral3ForConditionalGeneration
     kwargs['automodel_class'] = kwargs['automodel_class'] or Mistral3ForConditionalGeneration
     model, processor = get_model_tokenizer_multimodal(model_dir, model_info, model_kwargs, load_model, **kwargs)
 
@@ -184,4 +178,35 @@ def get_model_tokenizer_devstral_2505(model_dir: str,
         architectures=['Mistral3ForConditionalGeneration'],
         model_arch=ModelArch.llava_hf,
         requires=['transformers>=4.49'],
-    ), )
+    ))
+
+
+def get_model_tokenizer_mistral_2506(model_dir: str,
+                                     model_info: ModelInfo,
+                                     model_kwargs: Dict[str, Any],
+                                     load_model: bool = True,
+                                     **kwargs):
+    from mistral_common.tokens.tokenizers.mistral import MistralTokenizer
+    from transformers import Mistral3ForConditionalGeneration
+    tokenizer_dir = safe_snapshot_download('mistralai/Mistral-Small-3.1-24B-Instruct-2503', download_model=False)
+    processor = AutoProcessor.from_pretrained(tokenizer_dir)
+    kwargs['automodel_class'] = kwargs['automodel_class'] or Mistral3ForConditionalGeneration
+    kwargs['tokenizer'] = processor.tokenizer
+    model, _ = get_model_tokenizer_with_flash_attn(model_dir, model_info, model_kwargs, load_model, **kwargs)
+    return model, processor
+
+
+register_model(
+    ModelMeta(
+        MLLMModelType.mistral_2506,
+        [
+            ModelGroup([
+                Model('mistralai/Mistral-Small-3.2-24B-Instruct-2506', 'mistralai/Mistral-Small-3.2-24B-Instruct-2506'),
+            ]),
+        ],
+        TemplateType.mistral_2506,
+        get_model_tokenizer_mistral_2506,
+        architectures=['Mistral3ForConditionalGeneration'],
+        model_arch=ModelArch.llava_hf,
+        requires=['transformers>=4.49'],
+    ))

swift/llm/model/model_arch.py

@@ -81,7 +81,6 @@ class MLLMModelArch:
     megrez_omni = 'megrez_omni'
     valley = 'valley'
     gemma3n = 'gemma3n'
-    mistral_2503 = 'mistral_2503'
     keye_vl = 'keye_vl'
 
     midashenglm = 'midashenglm'

swift/llm/template/constant.py

@@ -229,6 +229,7 @@ class MLLMTemplateType:
     gemma3_vision = 'gemma3_vision'
     gemma3n = 'gemma3n'
     mistral_2503 = 'mistral_2503'
+    mistral_2506 = 'mistral_2506'
     paddle_ocr = 'paddle_ocr'
 
 

swift/llm/template/template/llm.py

@@ -119,29 +119,6 @@ def _preprocess_inputs(self, inputs: StdTemplateInputs) -> None:
         chat_sep=['</s>[INST] '],
         suffix=['</s>']))
 
-today = datetime.now().strftime('%Y-%m-%d')
-
-mistral_2501_system = (
-    'You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup '
-    'headquartered in Paris.\n'
-    f'Your knowledge base was last updated on 2023-10-01. The current date is {today}.\n\n'
-    "When you're not sure about some information, you say that you don't have the information and don't "
-    'make up anything.\n'
-    "If the user's question is not clear, ambiguous, or does not provide enough context for you to accurately answer "
-    'the question, you do not try to answer it right away and you rather ask the user to clarify their request (e.g. '
-    '"What are some good restaurants around me?" => "Where are you?" or "When is the next flight to Tokyo" => "'
-    'Where do you travel from?")')
-
-register_template(
-    TemplateMeta(
-        LLMTemplateType.mistral_2501,
-        prefix=['<s>'],
-        prompt=['[INST]{{QUERY}}[/INST]'],
-        chat_sep=['</s>'],
-        suffix=['</s>'],
-        system_prefix=['<s>[SYSTEM_PROMPT]{{SYSTEM}}[/SYSTEM_PROMPT]'],
-        default_system=mistral_2501_system))
-
 register_template(
     TemplateMeta(
         LLMTemplateType.xverse,

swift/llm/template/template/mistral.py

@@ -1,14 +1,39 @@
 # Copyright (c) Alibaba, Inc. and its affiliates.
+import os
+from dataclasses import dataclass, field
+from datetime import datetime, timedelta
 from typing import Any, Dict, List, Literal, Optional
 
-import torch
-
 from ..base import Template
-from ..constant import MLLMTemplateType
+from ..constant import LLMTemplateType, MLLMTemplateType
 from ..register import TemplateMeta, register_template
 from ..template_inputs import StdTemplateInputs
-from ..utils import Context, findall
-from .llm import mistral_2501_system
+from ..utils import Context, Prompt, findall
+
+today = datetime.now().strftime('%Y-%m-%d')
+
+mistral_2501_system = (
+    'You are Mistral Small 3, a Large Language Model (LLM) created by Mistral AI, a French startup '
+    'headquartered in Paris.\n'
+    f'Your knowledge base was last updated on 2023-10-01. The current date is {today}.\n\n'
+    "When you're not sure about some information, you say that you don't have the information and don't "
+    'make up anything.\n'
+    "If the user's question is not clear, ambiguous, or does not provide enough context for you to accurately answer "
+    'the question, you do not try to answer it right away and you rather ask the user to clarify their request (e.g. '
+    '"What are some good restaurants around me?" => "Where are you?" or "When is the next flight to Tokyo" => "'
+    'Where do you travel from?")')
+
+
+@dataclass
+class Mistral3TemplateMeta(TemplateMeta):
+    prefix: Prompt = field(default_factory=lambda: ['<s>'])
+    prompt: Prompt = field(default_factory=lambda: ['[INST]{{QUERY}}[/INST]'])
+    chat_sep: Optional[Prompt] = field(default_factory=lambda: ['</s>'])
+    suffix: Prompt = field(default_factory=lambda: ['</s>'])
+    system_prefix: Optional[Prompt] = field(default_factory=lambda: ['<s>[SYSTEM_PROMPT]{{SYSTEM}}[/SYSTEM_PROMPT]'])
+
+
+register_template(Mistral3TemplateMeta(LLMTemplateType.mistral_2501, default_system=mistral_2501_system))
 
 
 class Mistral2503Template(Template):
@@ -28,15 +53,16 @@ def _encode(self, inputs: StdTemplateInputs) -> Dict[str, Any]:
         labels = encoded['labels']
         loss_scale = encoded.get('loss_scale', None)
         idx_list = findall(input_ids, self.image_token)
+        patch_size = processor.patch_size * processor.spatial_merge_size
         if idx_list:
-            image_inputs = processor.image_processor(images, patch_size=processor.patch_size, return_tensors='pt')
+            image_inputs = processor.image_processor(images, patch_size=patch_size, return_tensors='pt')
             encoded['pixel_values'] = image_inputs['pixel_values'].to(self.model_info.torch_dtype)
             encoded['image_sizes'] = image_sizes = image_inputs['image_sizes']
 
             def _get_new_tokens(i):
                 height, width = image_sizes[i]
-                num_height_tokens = height // (processor.patch_size * processor.spatial_merge_size)
-                num_width_tokens = width // (processor.patch_size * processor.spatial_merge_size)
+                num_height_tokens = height // patch_size
+                num_width_tokens = width // patch_size
                 replace_tokens = [[processor.image_token] * num_width_tokens + [processor.image_break_token]
                                   ] * num_height_tokens
                 # Flatten list
@@ -52,15 +78,8 @@ def _get_new_tokens(i):
 
 
 register_template(
-    TemplateMeta(
-        MLLMTemplateType.mistral_2503,
-        prefix=['<s>'],
-        prompt=['[INST]{{QUERY}}[/INST]'],
-        chat_sep=['</s>'],
-        suffix=['</s>'],
-        system_prefix=['<s>[SYSTEM_PROMPT]{{SYSTEM}}[/SYSTEM_PROMPT]'],
-        default_system=mistral_2501_system,
-        template_cls=Mistral2503Template))
+    Mistral3TemplateMeta(
+        MLLMTemplateType.mistral_2503, default_system=mistral_2501_system, template_cls=Mistral2503Template))
 
 devstral_small_2505_system = (  # from https://huggingface.co/mistralai/Devstral-Small-2505/blob/main/SYSTEM_PROMPT.txt
     'You are Devstral, a helpful agentic model trained by Mistral AI and using the OpenHands scaffold. '
@@ -122,12 +141,27 @@ def _get_new_tokens(i):
     'executing a plan from the user, please don\'t try to directly work around it. Instead, propose a new '
     'plan and confirm with the user before proceeding.\n</TROUBLESHOOTING>')
 
+register_template(Mistral3TemplateMeta('devstral', default_system=devstral_small_2505_system))
+
+
+class Mistral2506Template(Mistral2503Template):
+
+    def _get_mistral_system(self):
+        from swift.llm import get_model_name
+        model_dir = self.model_info.model_dir
+        model_name = get_model_name(model_dir)
+        file_path = os.path.join(model_dir, 'SYSTEM_PROMPT.txt')
+        with open(file_path, 'r') as file:
+            system_prompt = file.read()
+        today = datetime.today().strftime('%Y-%m-%d')
+        yesterday = (datetime.today() - timedelta(days=1)).strftime('%Y-%m-%d')
+        return system_prompt.format(name=model_name, today=today, yesterday=yesterday)
+
+    def _swift_encode(self, inputs: StdTemplateInputs):
+        if inputs.system is None:
+            inputs.system = self._get_mistral_system()
+        return super()._swift_encode(inputs)
+
+
 register_template(
-    TemplateMeta(
-        'devstral',
-        prefix=['<s>'],
-        prompt=['[INST]{{QUERY}}[/INST]'],  # the user query
-        chat_sep=['</s>'],
-        suffix=['</s>'],
-        system_prefix=['<s>[SYSTEM_PROMPT]{{SYSTEM}}[/SYSTEM_PROMPT]'],  # the system prompt
-        default_system=devstral_small_2505_system))
+    Mistral3TemplateMeta(MLLMTemplateType.mistral_2506, default_system=None, template_cls=Mistral2506Template))

tests/test_align/test_template/test_vision.py

@@ -1092,6 +1092,15 @@ def test_ernie_vl_thinking():
     assert response == '\n<think>\n' + response2
 
 
+def test_mistral_2506():
+    pt_engine = PtEngine('mistralai/Mistral-Small-3.2-24B-Instruct-2506')
+    response = _infer_model(pt_engine, messages=[{'role': 'user', 'content': 'describe the image.'}])
+    assert response[:200] == (
+        'The image features a close-up of a kitten with striking blue eyes. The kitten has a soft, '
+        'fluffy coat with a mix of white, gray, and brown fur. Its fur pattern includes distinct '
+        'stripes, particularly ')
+
+
 if __name__ == '__main__':
     from swift.llm import PtEngine, RequestConfig
     from swift.utils import get_logger, seed_everything
@@ -1168,4 +1177,5 @@ def test_ernie_vl_thinking():
     # test_llava_onevision1_5()
     # test_paddle_ocr()
     # test_ernie_vl()
-    test_ernie_vl_thinking()
+    # test_ernie_vl_thinking()
+    test_mistral_2506()