wehub-resource-sync
349 lines
17 KiB
Python
349 lines
17 KiB
Python
# Copyright (c) ModelScope Contributors. All rights reserved.
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import os
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import sys
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from transformers import PreTrainedModel
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from swift.template import TemplateType
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from swift.utils import get_device, git_clone_github
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from ..constant import LLMModelType, MLLMModelType
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from ..model_arch import ModelArch
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from ..model_meta import Model, ModelGroup, ModelMeta
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from ..register import ModelLoader, register_model
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class LlamaLoader(ModelLoader):
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def get_config(self, model_dir):
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config = super().get_config(model_dir)
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if getattr(config, 'pretraining_tp', 1) > 1:
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config.pretraining_tp = 1
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return config
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register_model(
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ModelMeta(
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LLMModelType.llama,
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[
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# llama2
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ModelGroup(
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[
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# base
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Model('modelscope/Llama-2-7b-ms', 'meta-llama/Llama-2-7b-hf'),
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Model('modelscope/Llama-2-13b-ms', 'meta-llama/Llama-2-13b-hf'),
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Model('modelscope/Llama-2-70b-ms', 'meta-llama/Llama-2-70b-hf'),
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# chat
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Model('modelscope/Llama-2-7b-chat-ms', 'meta-llama/Llama-2-7b-chat-hf'),
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Model('modelscope/Llama-2-13b-chat-ms', 'meta-llama/Llama-2-13b-chat-hf'),
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Model('modelscope/Llama-2-70b-chat-ms', 'meta-llama/Llama-2-70b-chat-hf'),
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],
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TemplateType.llama,
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ignore_patterns=[r'.+\.bin$']),
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# chinese-llama2
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ModelGroup(
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[
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# base
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Model('AI-ModelScope/chinese-llama-2-1.3b', 'hfl/chinese-llama-2-1.3b'),
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Model('AI-ModelScope/chinese-llama-2-7b', 'hfl/chinese-llama-2-7b'),
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Model('AI-ModelScope/chinese-llama-2-7b-16k', 'hfl/chinese-llama-2-7b-16k'),
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Model('AI-ModelScope/chinese-llama-2-7b-64k', 'hfl/chinese-llama-2-7b-64k'),
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Model('AI-ModelScope/chinese-llama-2-13b', 'hfl/chinese-llama-2-13b'),
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Model('AI-ModelScope/chinese-llama-2-13b-16k', 'hfl/chinese-llama-2-13b-16k'),
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# chat
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Model('AI-ModelScope/chinese-alpaca-2-1.3b', 'hfl/chinese-alpaca-2-1.3b'),
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Model('AI-ModelScope/chinese-alpaca-2-7b', 'hfl/chinese-alpaca-2-7b'),
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Model('AI-ModelScope/chinese-alpaca-2-7b-16k', 'hfl/chinese-alpaca-2-7b-16k'),
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Model('AI-ModelScope/chinese-alpaca-2-7b-64k', 'hfl/chinese-alpaca-2-7b-64k'),
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Model('AI-ModelScope/chinese-alpaca-2-13b', 'hfl/chinese-alpaca-2-13b'),
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Model('AI-ModelScope/chinese-alpaca-2-13b-16k', 'hfl/chinese-alpaca-2-13b-16k'),
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],
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TemplateType.llama),
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# base quant
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ModelGroup([
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Model('AI-ModelScope/Llama-2-7b-AQLM-2Bit-1x16-hf', 'ISTA-DASLab/Llama-2-7b-AQLM-2Bit-1x16-hf'),
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],
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TemplateType.llama,
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requires=['transformers>=4.38', 'aqlm', 'torch>=2.2.0']),
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ModelGroup([
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Model('FlagAlpha/Atom-7B', 'FlagAlpha/Atom-7B'),
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Model('FlagAlpha/Atom-7B-Chat', 'FlagAlpha/Atom-7B-Chat'),
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],
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template=TemplateType.atom),
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ModelGroup([
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Model('langboat/Mengzi3-13B-Base', 'Langboat/Mengzi3-13B-Base'),
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],
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template=TemplateType.mengzi),
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ModelGroup([
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Model('AI-ModelScope/NuminaMath-7B-TIR', 'AI-MO/NuminaMath-7B-TIR'),
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],
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template=TemplateType.numina,
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tags=['math']),
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ModelGroup([
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Model('Fengshenbang/Ziya2-13B-Base', 'IDEA-CCNL/Ziya2-13B-Base'),
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Model('Fengshenbang/Ziya2-13B-Chat', 'IDEA-CCNL/Ziya2-13B-Chat'),
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],
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template=TemplateType.ziya),
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ModelGroup([
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Model('InfiniAI/Megrez-3b-Instruct', 'Infinigence/Megrez-3B-Instruct'),
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], TemplateType.megrez),
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# deepseek
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ModelGroup([
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Model('deepseek-ai/deepseek-llm-7b-base', 'deepseek-ai/deepseek-llm-7b-base'),
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Model('deepseek-ai/deepseek-llm-7b-chat', 'deepseek-ai/deepseek-llm-7b-chat'),
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Model('deepseek-ai/deepseek-llm-67b-base', 'deepseek-ai/deepseek-llm-67b-base'),
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Model('deepseek-ai/deepseek-llm-67b-chat', 'deepseek-ai/deepseek-llm-67b-chat'),
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], TemplateType.deepseek),
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ModelGroup(
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[
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Model('deepseek-ai/deepseek-math-7b-base', 'deepseek-ai/deepseek-math-7b-base'),
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Model('deepseek-ai/deepseek-math-7b-instruct', 'deepseek-ai/deepseek-math-7b-instruct'),
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Model('deepseek-ai/deepseek-math-7b-rl', 'deepseek-ai/deepseek-math-7b-rl'),
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],
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TemplateType.deepseek,
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tags=['math'],
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),
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ModelGroup(
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[
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Model('deepseek-ai/deepseek-coder-1.3b-base', 'deepseek-ai/deepseek-coder-1.3b-base'),
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Model('deepseek-ai/deepseek-coder-1.3b-instruct', 'deepseek-ai/deepseek-coder-1.3b-instruct'),
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Model('deepseek-ai/deepseek-coder-6.7b-base', 'deepseek-ai/deepseek-coder-6.7b-base'),
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Model('deepseek-ai/deepseek-coder-6.7b-instruct', 'deepseek-ai/deepseek-coder-6.7b-instruct'),
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Model('deepseek-ai/deepseek-coder-33b-base', 'deepseek-ai/deepseek-coder-33b-base'),
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Model('deepseek-ai/deepseek-coder-33b-instruct', 'deepseek-ai/deepseek-coder-33b-instruct'),
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],
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TemplateType.deepseek,
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tags=['coding'],
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),
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# MiniMind2
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ModelGroup(
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[
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# MiniMind2
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Model('gongjy/MiniMind2', 'jingyaogong/MiniMind2'),
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# MiniMind2-Small
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Model(None, 'jingyaogong/MiniMind2-Small'),
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],
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TemplateType.minimind,
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requires=['transformers>=4.57.1']),
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# llama3
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ModelGroup(
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[
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# chat
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Model('LLM-Research/Meta-Llama-3-8B-Instruct', 'meta-llama/Meta-Llama-3-8B-Instruct'),
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Model('LLM-Research/Meta-Llama-3-70B-Instruct', 'meta-llama/Meta-Llama-3-70B-Instruct'),
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# base
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Model('LLM-Research/Meta-Llama-3-8B', 'meta-llama/Meta-Llama-3-8B'),
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Model('LLM-Research/Meta-Llama-3-70B', 'meta-llama/Meta-Llama-3-70B'),
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],
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TemplateType.llama3),
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# llama3-quant
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ModelGroup([
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Model('swift/Meta-Llama-3-8B-Instruct-GPTQ-Int4', 'study-hjt/Meta-Llama-3-8B-Instruct-GPTQ-Int4'),
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Model('swift/Meta-Llama-3-8B-Instruct-GPTQ-Int8', 'study-hjt/Meta-Llama-3-8B-Instruct-GPTQ-Int8'),
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Model('swift/Meta-Llama-3-8B-Instruct-AWQ', 'study-hjt/Meta-Llama-3-8B-Instruct-AWQ'),
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Model('swift/Meta-Llama-3-70B-Instruct-GPTQ-Int4', 'study-hjt/Meta-Llama-3-70B-Instruct-GPTQ-Int4'),
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Model('swift/Meta-Llama-3-70B-Instruct-GPTQ-Int8', 'study-hjt/Meta-Llama-3-70B-Instruct-GPTQ-Int8'),
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Model('swift/Meta-Llama-3-70B-Instruct-AWQ', 'study-hjt/Meta-Llama-3-70B-Instruct-AWQ'),
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], TemplateType.llama3),
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# chinese-llama3
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ModelGroup([
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Model('ChineseAlpacaGroup/llama-3-chinese-8b-instruct', 'hfl/llama-3-chinese-8b-instruct'),
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Model('ChineseAlpacaGroup/llama-3-chinese-8b', 'hfl/llama-3-chinese-8b'),
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], TemplateType.llama3),
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# llama3.1
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ModelGroup(
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[
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# chat
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Model('LLM-Research/Meta-Llama-3.1-8B-Instruct', 'meta-llama/Meta-Llama-3.1-8B-Instruct'),
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Model('LLM-Research/Meta-Llama-3.1-70B-Instruct', 'meta-llama/Meta-Llama-3.1-70B-Instruct'),
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Model('LLM-Research/Meta-Llama-3.1-405B-Instruct', 'meta-llama/Meta-Llama-3.1-405B-Instruct'),
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# base
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Model('LLM-Research/Meta-Llama-3.1-8B', 'meta-llama/Meta-Llama-3.1-8B'),
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Model('LLM-Research/Meta-Llama-3.1-70B', 'meta-llama/Meta-Llama-3.1-70B'),
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Model('LLM-Research/Meta-Llama-3.1-405B', 'meta-llama/Meta-Llama-3.1-405B'),
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# fp8
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Model('LLM-Research/Meta-Llama-3.1-70B-Instruct-FP8', 'meta-llama/Meta-Llama-3.1-70B-Instruct-FP8'),
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Model('LLM-Research/Meta-Llama-3.1-405B-Instruct-FP8',
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'meta-llama/Meta-Llama-3.1-405B-Instruct-FP8'),
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],
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TemplateType.llama3_2,
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requires=['transformers>=4.43']),
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# llama3.1-quant
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ModelGroup(
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[
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# bnb-nf4
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Model('LLM-Research/Meta-Llama-3.1-8B-Instruct-BNB-NF4',
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'hugging-quants/Meta-Llama-3.1-8B-Instruct-BNB-NF4'),
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Model('LLM-Research/Meta-Llama-3.1-70B-Instruct-bnb-4bit',
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'unsloth/Meta-Llama-3.1-70B-Instruct-bnb-4bit'),
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Model('LLM-Research/Meta-Llama-3.1-405B-Instruct-BNB-NF4',
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'hugging-quants/Meta-Llama-3.1-405B-Instruct-BNB-NF4'),
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# gptq-int4
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Model('LLM-Research/Meta-Llama-3.1-8B-Instruct-GPTQ-INT4',
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'hugging-quants/Meta-Llama-3.1-8B-Instruct-GPTQ-INT4'),
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Model('LLM-Research/Meta-Llama-3.1-70B-Instruct-GPTQ-INT4',
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'hugging-quants/Meta-Llama-3.1-70B-Instruct-GPTQ-INT4'),
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Model('LLM-Research/Meta-Llama-3.1-405B-Instruct-GPTQ-INT4',
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'hugging-quants/Meta-Llama-3.1-405B-Instruct-GPTQ-INT4'),
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# awq-int4
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Model('LLM-Research/Meta-Llama-3.1-8B-Instruct-AWQ-INT4',
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'hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4'),
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Model('LLM-Research/Meta-Llama-3.1-70B-Instruct-AWQ-INT4',
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'hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-INT4'),
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Model('LLM-Research/Meta-Llama-3.1-405B-Instruct-AWQ-INT4',
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'hugging-quants/Meta-Llama-3.1-405B-Instruct-AWQ-INT4'),
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],
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TemplateType.llama3_2,
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requires=['transformers>=4.43']),
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# nvidia Nemotron
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ModelGroup([
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Model('AI-ModelScope/Llama-3.1-Nemotron-70B-Instruct-HF', 'nvidia/Llama-3.1-Nemotron-70B-Instruct-HF'),
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],
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TemplateType.llama3_2,
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requires=['transformers>=4.43']),
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ModelGroup([
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Model('AI-ModelScope/Skywork-o1-Open-Llama-3.1-8B', 'Skywork/Skywork-o1-Open-Llama-3.1-8B'),
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],
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TemplateType.skywork_o1,
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requires=['transformers>=4.43']),
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ModelGroup([
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Model('LLM-Research/Llama-3.2-1B', 'meta-llama/Llama-3.2-1B'),
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Model('LLM-Research/Llama-3.2-3B', 'meta-llama/Llama-3.2-3B'),
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Model('LLM-Research/Llama-3.2-1B-Instruct', 'meta-llama/Llama-3.2-1B-Instruct'),
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Model('LLM-Research/Llama-3.2-3B-Instruct', 'meta-llama/Llama-3.2-3B-Instruct'),
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],
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template=TemplateType.llama3_2,
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requires=['transformers>=4.43']),
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ModelGroup([
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Model('LLM-Research/Llama-3.3-70B-Instruct', 'meta-llama/Llama-3.3-70B-Instruct'),
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Model('unsloth/Llama-3.3-70B-Instruct-bnb-4bit', 'unsloth/Llama-3.3-70B-Instruct-bnb-4bit'),
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],
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template=TemplateType.llama3_2,
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requires=['transformers>=4.43']),
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ModelGroup([
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Model('ZhipuAI/LongWriter-llama3.1-8b', 'zai-org/LongWriter-llama3.1-8b'),
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],
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TemplateType.longwriter_llama,
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requires=['transformers>=4.43']),
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ModelGroup([
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Model('deepseek-ai/DeepSeek-R1-Distill-Llama-8B', 'deepseek-ai/DeepSeek-R1-Distill-Llama-8B'),
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Model('deepseek-ai/DeepSeek-R1-Distill-Llama-70B', 'deepseek-ai/DeepSeek-R1-Distill-Llama-70B'),
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], TemplateType.deepseek_r1),
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# MiniCPM5
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ModelGroup([
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Model('OpenBMB/MiniCPM5-1B', 'openbmb/MiniCPM5-1B'),
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Model('OpenBMB/MiniCPM5-1B-Base', 'openbmb/MiniCPM5-1B-Base'),
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Model('OpenBMB/MiniCPM5-1B-SFT', 'openbmb/MiniCPM5-1B-SFT'),
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],
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TemplateType.minicpm5,
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requires=['transformers>=5.6']),
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ModelGroup([
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Model('LLM-Research/Reflection-Llama-3.1-70B', 'mattshumer/Reflection-Llama-3.1-70B'),
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],
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TemplateType.reflection,
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requires=['transformers>=4.43']),
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],
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LlamaLoader,
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model_arch=ModelArch.llama,
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architectures=['LlamaForCausalLM'],
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))
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class Llama3_2VisionLoader(ModelLoader):
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def get_model(self, model_dir: str, *args, **kwargs) -> PreTrainedModel:
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from transformers import MllamaForConditionalGeneration
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self.auto_model_cls = self.auto_model_cls or MllamaForConditionalGeneration
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return super().get_model(model_dir, *args, **kwargs)
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register_model(
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ModelMeta(
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MLLMModelType.llama3_2_vision,
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[
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ModelGroup([
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Model('LLM-Research/Llama-3.2-11B-Vision-Instruct', 'meta-llama/Llama-3.2-11B-Vision-Instruct'),
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Model('LLM-Research/Llama-3.2-90B-Vision-Instruct', 'meta-llama/Llama-3.2-90B-Vision-Instruct'),
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Model('LLM-Research/Llama-3.2-11B-Vision', 'meta-llama/Llama-3.2-11B-Vision'),
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Model('LLM-Research/Llama-3.2-90B-Vision', 'meta-llama/Llama-3.2-90B-Vision'),
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])
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],
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Llama3_2VisionLoader,
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template=TemplateType.llama3_2_vision,
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requires=['transformers>=4.45'],
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architectures=['MllamaForConditionalGeneration'],
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model_arch=ModelArch.llama3_2_vision,
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tags=['vision'],
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))
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class Llama4Loader(ModelLoader):
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def get_model(self, model_dir: str, *args, **kwargs) -> PreTrainedModel:
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from transformers import Llama4ForConditionalGeneration
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self.auto_model_cls = self.auto_model_cls or Llama4ForConditionalGeneration
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return super().get_model(model_dir, *args, **kwargs)
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register_model(
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ModelMeta(
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MLLMModelType.llama4,
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[
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ModelGroup([
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Model('LLM-Research/Llama-4-Scout-17B-16E', 'meta-llama/Llama-4-Scout-17B-16E'),
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Model('LLM-Research/Llama-4-Maverick-17B-128E', 'meta-llama/Llama-4-Maverick-17B-128E'),
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Model('LLM-Research/Llama-4-Scout-17B-16E-Instruct', 'meta-llama/Llama-4-Scout-17B-16E-Instruct'),
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Model('LLM-Research/Llama-4-Maverick-17B-128E-Instruct-FP8',
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'meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8'),
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Model('LLM-Research/Llama-4-Maverick-17B-128E-Instruct',
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'meta-llama/Llama-4-Maverick-17B-128E-Instruct'),
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])
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],
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Llama4Loader,
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template=TemplateType.llama4,
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requires=['transformers>=4.51'],
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model_arch=ModelArch.llama4,
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architectures=['Llama4ForConditionalGeneration'],
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tags=['vision'],
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))
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class Llama3OmniLoader(ModelLoader):
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def get_model(self, model_dir: str, config, processor, model_kwargs) -> PreTrainedModel:
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local_repo_path = self.local_repo_path
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if not local_repo_path:
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local_repo_path = git_clone_github('https://github.com/ictnlp/LLaMA-Omni')
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sys.path.append(self.local_repo_path)
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import whisper
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from omni_speech.model import OmniSpeech2SLlamaForCausalLM, OmniSpeechLlamaForCausalLM
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config.speech_encoder = os.path.join(model_dir, 'large-v3.pt')
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if not os.path.exists(config.speech_encoder):
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whisper.load_model('large-v3', download_root=model_dir)
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self.auto_model_cls = self.auto_model_cls or OmniSpeech2SLlamaForCausalLM
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for key in ['forward', 'generate']:
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try:
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delattr(OmniSpeech2SLlamaForCausalLM, key)
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delattr(OmniSpeechLlamaForCausalLM, key)
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except AttributeError:
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pass
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# not support device_map='auto'
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device_map = model_kwargs['device_map']
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model_kwargs['device_map'] = None
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model = super().get_model(model_dir, config, processor, model_kwargs)
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model.to(get_device() if device_map == 'auto' else device_map)
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return model
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register_model(
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ModelMeta(
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MLLMModelType.llama3_1_omni,
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[ModelGroup([
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Model('ICTNLP/Llama-3.1-8B-Omni', 'ICTNLP/Llama-3.1-8B-Omni'),
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], )],
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Llama3OmniLoader,
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template=TemplateType.llama3_1_omni,
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architectures=['OmniSpeech2SLlamaForCausalLM'],
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model_arch=ModelArch.llama3_1_omni,
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requires=['openai-whisper'],
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tags=['audio'],
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))
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