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# Copyright (c) ModelScope Contributors. All rights reserved.
from transformers import AutoProcessor, AutoTokenizer, PretrainedConfig, PreTrainedModel
from typing import Any, Dict
from swift.template import TemplateType
from swift.utils import Processor, safe_snapshot_download
from ..constant import LLMModelType, MLLMModelType
from ..model_arch import ModelArch
from ..model_meta import Model, ModelGroup, ModelMeta
from ..register import ModelLoader, register_model
register_model(
ModelMeta(
LLMModelType.mistral,
[
ModelGroup([
Model('AI-ModelScope/Mistral-7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.1'),
Model('AI-ModelScope/Mistral-7B-Instruct-v0.2', 'mistralai/Mistral-7B-Instruct-v0.2'),
Model('LLM-Research/Mistral-7B-Instruct-v0.3', 'mistralai/Mistral-7B-Instruct-v0.3'),
Model('AI-ModelScope/Mistral-7B-v0.1', 'mistralai/Mistral-7B-v0.1'),
Model('AI-ModelScope/Mistral-7B-v0.2-hf', 'alpindale/Mistral-7B-v0.2-hf'),
]),
ModelGroup([
Model('swift/Codestral-22B-v0.1', 'mistralai/Codestral-22B-v0.1'),
]),
],
template=TemplateType.llama,
architectures=['MistralForCausalLM'],
model_arch=ModelArch.llama,
requires=['transformers>=4.34'],
))
register_model(
ModelMeta(
LLMModelType.mixtral, [
ModelGroup([
Model('AI-ModelScope/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mixtral-8x7B-Instruct-v0.1'),
Model('AI-ModelScope/Mixtral-8x7B-v0.1', 'mistralai/Mixtral-8x7B-v0.1'),
Model('AI-ModelScope/Mixtral-8x22B-v0.1', 'mistral-community/Mixtral-8x22B-v0.1'),
],
requires=['transformers>=4.36']),
ModelGroup([
Model('AI-ModelScope/Mixtral-8x7b-AQLM-2Bit-1x16-hf', 'ISTA-DASLab/Mixtral-8x7b-AQLM-2Bit-1x16-hf'),
],
requires=['transformers>=4.38', 'aqlm', 'torch>=2.2.0']),
],
template=TemplateType.llama,
architectures=['MixtralForCausalLM'],
model_arch=ModelArch.llama))
register_model(
ModelMeta(
LLMModelType.mistral_nemo, [
ModelGroup([
Model('AI-ModelScope/Mistral-Small-Instruct-2409', 'mistralai/Mistral-Small-Instruct-2409'),
Model('LLM-Research/Mistral-Large-Instruct-2407', 'mistralai/Mistral-Large-Instruct-2407'),
Model('AI-ModelScope/Mistral-Nemo-Base-2407', 'mistralai/Mistral-Nemo-Base-2407'),
Model('AI-ModelScope/Mistral-Nemo-Instruct-2407', 'mistralai/Mistral-Nemo-Instruct-2407'),
],
requires=['transformers>=4.43']),
ModelGroup([
Model('AI-ModelScope/Ministral-8B-Instruct-2410', 'mistralai/Ministral-8B-Instruct-2410'),
],
requires=['transformers>=4.46']),
],
template=TemplateType.mistral_nemo,
architectures=['MistralForCausalLM'],
model_arch=ModelArch.llama))
register_model(
ModelMeta(
LLMModelType.mistral_2501, [
ModelGroup([
Model('mistralai/Mistral-Small-24B-Base-2501', 'mistralai/Mistral-Small-24B-Base-2501'),
Model('mistralai/Mistral-Small-24B-Instruct-2501', 'mistralai/Mistral-Small-24B-Instruct-2501'),
]),
],
template=TemplateType.mistral_2501,
architectures=['MistralForCausalLM'],
model_arch=ModelArch.llama))
register_model(
ModelMeta(
LLMModelType.zephyr,
[
ModelGroup([
Model('modelscope/zephyr-7b-beta', 'HuggingFaceH4/zephyr-7b-beta'),
]),
],
template=TemplateType.zephyr,
model_arch=ModelArch.llama,
architectures=['MistralForCausalLM'],
requires=['transformers>=4.34'],
))
register_model(
ModelMeta(
LLMModelType.wizardlm2_moe,
[ModelGroup([
Model('AI-ModelScope/WizardLM-2-8x22B', 'alpindale/WizardLM-2-8x22B'),
])],
template=TemplateType.wizardlm2_moe,
architectures=['MixtralForCausalLM'],
requires=['transformers>=4.36'],
))
register_model(
ModelMeta(
LLMModelType.wizardlm2,
[ModelGroup([
Model('AI-ModelScope/WizardLM-2-7B-AWQ', 'MaziyarPanahi/WizardLM-2-7B-AWQ'),
])],
template=TemplateType.wizardlm2,
architectures=['MistralForCausalLM'],
requires=['transformers>=4.34'],
))
class DevstralLoader(ModelLoader):
def get_processor(self, model_dir: str, config: PretrainedConfig) -> Processor:
# src: sglang did the same (https://github.com/sgl-project/sglang/pull/6547)
tokenizer_dir = safe_snapshot_download('mistralai/Mistral-Small-3.1-24B-Instruct-2503', download_model=False)
tokenizer = AutoTokenizer.from_pretrained(tokenizer_dir)
return tokenizer
register_model(
ModelMeta(
LLMModelType.devstral, [
ModelGroup([
Model('mistralai/Devstral-Small-2505', 'mistralai/Devstral-Small-2505'),
],
requires=['transformers>=4.43', 'mistral-common>=1.5.5'])
],
DevstralLoader,
template=TemplateType.devstral,
architectures=['MistralForCausalLM'],
model_arch=ModelArch.llama))
class Mistral3Loader(ModelLoader):
def get_model(self, model_dir: str, *args, **kwargs) -> PreTrainedModel:
from transformers import Mistral3ForConditionalGeneration
self.auto_model_cls = self.auto_model_cls or Mistral3ForConditionalGeneration
return super().get_model(model_dir, *args, **kwargs)
register_model(
ModelMeta(
MLLMModelType.mistral3,
[
ModelGroup([
Model('mistralai/Mistral-Small-3.1-24B-Base-2503', 'mistralai/Mistral-Small-3.1-24B-Base-2503'),
Model('mistralai/Mistral-Small-3.1-24B-Instruct-2503', 'mistralai/Mistral-Small-3.1-24B-Instruct-2503'),
],
requires=['transformers>=4.49']),
ModelGroup([
Model('mistralai/Ministral-3-3B-Base-2512', 'mistralai/Ministral-3-3B-Base-2512'),
Model('mistralai/Ministral-3-3B-Instruct-2512', 'mistralai/Ministral-3-3B-Instruct-2512'),
Model('mistralai/Ministral-3-3B-Instruct-2512-BF16', 'mistralai/Ministral-3-3B-Instruct-2512-BF16'),
Model('mistralai/Ministral-3-8B-Base-2512', 'mistralai/Ministral-3-8B-Base-2512'),
Model('mistralai/Ministral-3-8B-Instruct-2512', 'mistralai/Ministral-3-8B-Instruct-2512'),
Model('mistralai/Ministral-3-8B-Instruct-2512-BF16', 'mistralai/Ministral-3-8B-Instruct-2512-BF16'),
Model('mistralai/Ministral-3-14B-Base-2512', 'mistralai/Ministral-3-14B-Base-2512'),
Model('mistralai/Ministral-3-14B-Instruct-2512', 'mistralai/Ministral-3-14B-Instruct-2512'),
Model('mistralai/Ministral-3-14B-Instruct-2512-BF16', 'mistralai/Ministral-3-14B-Instruct-2512-BF16'),
],
TemplateType.mistral_2512,
requires=['transformers>=5.0.0.dev0', 'mistral-common>=1.8.6']),
ModelGroup([
Model('mistralai/Ministral-3-3B-Reasoning-2512', 'mistralai/Ministral-3-3B-Reasoning-2512'),
Model('mistralai/Ministral-3-8B-Reasoning-2512', 'mistralai/Ministral-3-8B-Reasoning-2512'),
Model('mistralai/Ministral-3-14B-Reasoning-2512', 'mistralai/Ministral-3-14B-Reasoning-2512'),
],
TemplateType.mistral_2512_thinking,
requires=['transformers>=5.0.0.dev0', 'mistral-common>=1.8.6']),
],
Mistral3Loader,
template=TemplateType.mistral_2503,
model_arch=ModelArch.llava_hf,
architectures=['Mistral3ForConditionalGeneration'],
tags=['vision'],
ignore_patterns=[],
))
class Mistral3_2506Loader(Mistral3Loader):
def get_processor(self, model_dir: str, config: PretrainedConfig) -> Processor:
tokenizer_dir = safe_snapshot_download('mistralai/Mistral-Small-3.1-24B-Instruct-2503', download_model=False)
processor = AutoProcessor.from_pretrained(tokenizer_dir)
return processor
register_model(
ModelMeta(
MLLMModelType.mistral3_2506,
[
ModelGroup([
Model('mistralai/Mistral-Small-3.2-24B-Instruct-2506', 'mistralai/Mistral-Small-3.2-24B-Instruct-2506'),
]),
],
Mistral3_2506Loader,
template=TemplateType.mistral_2506,
architectures=['Mistral3ForConditionalGeneration'],
model_arch=ModelArch.llava_hf,
requires=['transformers>=4.49'],
))