wehub-resource-sync
442 lines
16 KiB
Python
442 lines
16 KiB
Python
# Copyright (c) ModelScope Contributors. All rights reserved.
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from transformers import AutoTokenizer, PretrainedConfig
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from typing import Any, Dict
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from swift.template import TemplateType
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from swift.utils import Processor, get_logger, safe_snapshot_download
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from ..constant import LLMModelType
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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, SentenceTransformersLoader, register_model
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logger = get_logger()
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class GrokLoader(ModelLoader):
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def get_processor(self, model_dir: str, config: PretrainedConfig) -> Processor:
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tokenizer_dir = safe_snapshot_download('AI-ModelScope/grok-1-tokenizer', download_model=False, check_local=True)
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tokenizer = AutoTokenizer.from_pretrained(tokenizer_dir, trust_remote_code=True)
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return tokenizer
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register_model(
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ModelMeta(
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LLMModelType.grok, [
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ModelGroup([
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Model('colossalai/grok-1-pytorch', 'hpcai-tech/grok-1'),
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]),
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],
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GrokLoader,
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template=TemplateType.default,
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architectures=['Grok1ModelForCausalLM'],
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model_arch=ModelArch.llama))
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class PolyLMLoader(ModelLoader):
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def get_processor(self, model_dir: str, config: PretrainedConfig) -> Processor:
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return AutoTokenizer.from_pretrained(model_dir, trust_remote_code=True, use_fast=False, legacy=True)
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register_model(
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ModelMeta(
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LLMModelType.polylm,
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[
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ModelGroup(
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[
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# base
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Model('damo/nlp_polylm_13b_text_generation', 'DAMO-NLP-MT/polylm-13b'),
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], ),
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],
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PolyLMLoader,
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template=TemplateType.default,
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architectures=['GPT2LMHeadModel'],
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model_arch=ModelArch.qwen))
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class YuanLoader(ModelLoader):
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def get_processor(self, model_dir: str, config: PretrainedConfig) -> Processor:
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tokenizer = AutoTokenizer.from_pretrained(
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model_dir, add_eos_token=False, add_bos_token=False, eos_token='<eod>', legacy=True)
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addi_tokens = [
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'<sep>', '<pad>', '<mask>', '<predict>', '<FIM_SUFFIX>', '<FIM_PREFIX>', '<FIM_MIDDLE>', '<commit_before>',
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'<commit_msg>', '<commit_after>', '<jupyter_start>', '<jupyter_text>', '<jupyter_code>', '<jupyter_output>',
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'<empty_output>'
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]
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tokenizer.add_tokens(addi_tokens, special_tokens=True)
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return tokenizer
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register_model(
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ModelMeta(
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LLMModelType.yuan2,
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[
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ModelGroup([
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Model('IEITYuan/Yuan2.0-2B-hf', 'IEITYuan/Yuan2-2B-hf'),
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Model('IEITYuan/Yuan2.0-51B-hf', 'IEITYuan/Yuan2-51B-hf'),
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Model('IEITYuan/Yuan2.0-102B-hf', 'IEITYuan/Yuan2-102B-hf'),
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Model('IEITYuan/Yuan2-2B-Janus-hf', 'IEITYuan/Yuan2-2B-Janus-hf'),
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]),
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ModelGroup([
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Model('IEITYuan/Yuan2-M32-hf', 'IEITYuan/Yuan2-M32-hf'),
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]),
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],
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YuanLoader,
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template=TemplateType.yuan,
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model_arch=ModelArch.llama,
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architectures=['YuanForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.orion,
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[
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ModelGroup([
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Model('OrionStarAI/Orion-14B-Chat', 'OrionStarAI/Orion-14B-Chat'),
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Model('OrionStarAI/Orion-14B-Base', 'OrionStarAI/Orion-14B-Base'),
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]),
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],
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template=TemplateType.orion,
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model_arch=ModelArch.llama,
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architectures=['OrionForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.dbrx, [
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ModelGroup([
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Model('AI-ModelScope/dbrx-base', 'databricks/dbrx-base'),
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Model('AI-ModelScope/dbrx-instruct', 'databricks/dbrx-instruct'),
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]),
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],
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template=TemplateType.dbrx,
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model_arch=ModelArch.dbrx,
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architectures=['DbrxForCausalLM'],
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requires=['transformers>=4.36']))
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register_model(
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ModelMeta(
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LLMModelType.bluelm,
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[
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ModelGroup([
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Model('vivo-ai/BlueLM-7B-Chat-32K', 'vivo-ai/BlueLM-7B-Chat-32K'),
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Model('vivo-ai/BlueLM-7B-Chat', 'vivo-ai/BlueLM-7B-Chat'),
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Model('vivo-ai/BlueLM-7B-Base-32K', 'vivo-ai/BlueLM-7B-Base-32K'),
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Model('vivo-ai/BlueLM-7B-Base', 'vivo-ai/BlueLM-7B-Base'),
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]),
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],
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template=TemplateType.bluelm,
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model_arch=ModelArch.llama,
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architectures=['BlueLMForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.seggpt,
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[
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ModelGroup([
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Model('damo/nlp_seqgpt-560m', 'DAMO-NLP/SeqGPT-560M'),
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]),
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],
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template=TemplateType.default,
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model_arch=None,
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architectures=['BloomForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.xverse,
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[
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ModelGroup([
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Model('xverse/XVERSE-7B-Chat', 'xverse/XVERSE-7B-Chat'),
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Model('xverse/XVERSE-7B', 'xverse/XVERSE-7B'),
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Model('xverse/XVERSE-13B', 'xverse/XVERSE-13B'),
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Model('xverse/XVERSE-13B-Chat', 'xverse/XVERSE-13B-Chat'),
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Model('xverse/XVERSE-65B', 'xverse/XVERSE-65B'),
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Model('xverse/XVERSE-65B-2', 'xverse/XVERSE-65B-2'),
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Model('xverse/XVERSE-65B-Chat', 'xverse/XVERSE-65B-Chat'),
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Model('xverse/XVERSE-13B-256K', 'xverse/XVERSE-13B-256K', ms_revision='v1.0.0'),
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]),
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],
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template=TemplateType.xverse,
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model_arch=ModelArch.llama,
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architectures=['XverseForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.xverse_moe,
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[
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ModelGroup([
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Model('xverse/XVERSE-MoE-A4.2B', 'xverse/XVERSE-MoE-A4.2B'),
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]),
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],
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template=TemplateType.xverse,
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model_arch=ModelArch.llama,
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architectures=['XverseForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.c4ai,
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[
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ModelGroup([
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Model('AI-ModelScope/c4ai-command-r-v01', 'CohereForAI/c4ai-command-r-v01'),
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Model('AI-ModelScope/c4ai-command-r-plus', 'CohereForAI/c4ai-command-r-plus'),
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]),
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],
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template=TemplateType.c4ai,
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model_arch=ModelArch.llama,
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architectures=['CohereForCausalLM'],
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requires=['transformers>=4.39'],
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))
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register_model(
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ModelMeta(
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LLMModelType.aya, [
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ModelGroup([
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Model('AI-ModelScope/aya-expanse-8b', 'CohereForAI/aya-expanse-8b'),
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Model('AI-ModelScope/aya-expanse-32b', 'CohereForAI/aya-expanse-32b'),
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]),
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],
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template=TemplateType.aya,
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model_arch=ModelArch.llama,
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architectures=['CohereForCausalLM'],
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requires=['transformers>=4.44.0']))
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register_model(
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ModelMeta(
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LLMModelType.ling,
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[
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ModelGroup([
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Model('inclusionAI/Ling-lite', 'inclusionAI/Ling-lite'),
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Model('inclusionAI/Ling-plus', 'inclusionAI/Ling-plus'),
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Model('inclusionAI/Ling-lite-base', 'inclusionAI/Ling-lite-base'),
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Model('inclusionAI/Ling-plus-base', 'inclusionAI/Ling-plus-base'),
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]),
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],
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template=TemplateType.ling,
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architectures=['BailingMoeForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.qwen2_gte, [
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ModelGroup([
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Model('iic/gte_Qwen2-1.5B-instruct', 'Alibaba-NLP/gte-Qwen2-1.5B-instruct'),
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Model('iic/gte_Qwen2-7B-instruct', 'Alibaba-NLP/gte-Qwen2-7B-instruct'),
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]),
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],
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SentenceTransformersLoader,
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template=TemplateType.dummy,
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architectures=['Qwen2ForCausalLM']))
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register_model(
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ModelMeta(
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LLMModelType.mimo, [
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ModelGroup([
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Model('XiaomiMiMo/MiMo-7B-Base', 'XiaomiMiMo/MiMo-7B-Base'),
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Model('XiaomiMiMo/MiMo-7B-SFT', 'XiaomiMiMo/MiMo-7B-SFT'),
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Model('XiaomiMiMo/MiMo-7B-RL-Zero', 'XiaomiMiMo/MiMo-7B-RL-Zero'),
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Model('XiaomiMiMo/MiMo-7B-RL', 'XiaomiMiMo/MiMo-7B-RL'),
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], TemplateType.qwen),
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ModelGroup([
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Model('XiaomiMiMo/MiMo-7B-RL-0530', 'XiaomiMiMo/MiMo-7B-RL-0530'),
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], TemplateType.mimo_rl),
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],
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model_arch=ModelArch.llama,
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architectures=['MiMoForCausalLM'],
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requires=['transformers>=4.37']))
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register_model(
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ModelMeta(
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LLMModelType.dots1,
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[
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ModelGroup([
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Model('rednote-hilab/dots.llm1.base', 'rednote-hilab/dots.llm1.base'),
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Model('rednote-hilab/dots.llm1.inst', 'rednote-hilab/dots.llm1.inst'),
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])
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],
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template=TemplateType.dots1,
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architectures=['Dots1ForCausalLM'],
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requires=['transformers>=4.53'],
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))
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register_model(
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ModelMeta(
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LLMModelType.hunyuan,
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[ModelGroup([
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Model('Tencent-Hunyuan/Hunyuan-A13B-Instruct', 'tencent/Hunyuan-A13B-Instruct'),
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])],
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template=TemplateType.hunyuan_moe,
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architectures=['HunYuanMoEV1ForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.hunyuan_v1_dense,
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[
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ModelGroup([
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Model('Tencent-Hunyuan/Hunyuan-0.5B-Instruct', 'tencent/Hunyuan-0.5B-Instruct'),
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Model('Tencent-Hunyuan/Hunyuan-1.8B-Instruct', 'tencent/Hunyuan-1.8B-Instruct'),
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Model('Tencent-Hunyuan/Hunyuan-4B-Instruct', 'tencent/Hunyuan-4B-Instruct'),
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Model('Tencent-Hunyuan/Hunyuan-7B-Instruct', 'tencent/Hunyuan-7B-Instruct'),
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# pretrain
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Model('Tencent-Hunyuan/Hunyuan-0.5B-Pretrain', 'tencent/Hunyuan-0.5B-Pretrain'),
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Model('Tencent-Hunyuan/Hunyuan-1.8B-Pretrain', 'tencent/Hunyuan-1.8B-Pretrain'),
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Model('Tencent-Hunyuan/Hunyuan-4B-Pretrain', 'tencent/Hunyuan-4B-Pretrain'),
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Model('Tencent-Hunyuan/Hunyuan-7B-Pretrain', 'tencent/Hunyuan-7B-Pretrain'),
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# fp8
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Model('Tencent-Hunyuan/Hunyuan-0.5B-Instruct-FP8', 'tencent/Hunyuan-0.5B-Instruct-FP8'),
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Model('Tencent-Hunyuan/Hunyuan-1.8B-Instruct-FP8', 'tencent/Hunyuan-1.8B-Instruct-FP8'),
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Model('Tencent-Hunyuan/Hunyuan-4B-Instruct-FP8', 'tencent/Hunyuan-4B-Instruct-FP8'),
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Model('Tencent-Hunyuan/Hunyuan-7B-Instruct-FP8', 'tencent/Hunyuan-7B-Instruct-FP8'),
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# awq
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Model('Tencent-Hunyuan/Hunyuan-0.5B-Instruct-AWQ-Int4', 'tencent/Hunyuan-0.5B-Instruct-AWQ-Int4'),
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Model('Tencent-Hunyuan/Hunyuan-1.8B-Instruct-AWQ-Int4', 'tencent/Hunyuan-1.8B-Instruct-AWQ-Int4'),
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Model('Tencent-Hunyuan/Hunyuan-4B-Instruct-AWQ-Int4', 'tencent/Hunyuan-4B-Instruct-AWQ-Int4'),
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Model('Tencent-Hunyuan/Hunyuan-7B-Instruct-AWQ-Int4', 'tencent/Hunyuan-7B-Instruct-AWQ-Int4'),
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# gptq
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Model('Tencent-Hunyuan/Hunyuan-0.5B-Instruct-GPTQ-Int4', 'tencent/Hunyuan-0.5B-Instruct-GPTQ-Int4'),
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Model('Tencent-Hunyuan/Hunyuan-1.8B-Instruct-GPTQ-Int4', 'tencent/Hunyuan-1.8B-Instruct-GPTQ-Int4'),
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Model('Tencent-Hunyuan/Hunyuan-4B-Instruct-GPTQ-Int4', 'tencent/Hunyuan-4B-Instruct-GPTQ-Int4'),
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Model('Tencent-Hunyuan/Hunyuan-7B-Instruct-GPTQ-Int4', 'tencent/Hunyuan-7B-Instruct-GPTQ-Int4'),
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])
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],
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template=TemplateType.hunyuan,
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requires=['transformers>=4.55.0.dev0'],
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architectures=['HunYuanDenseV1ForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.hy_v3,
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[
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ModelGroup([
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Model('Tencent-Hunyuan/Hy3-preview', 'tencent/Hy3-preview'),
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Model('Tencent-Hunyuan/Hy3-preview-Base', 'tencent/Hy3-preview-Base'),
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],
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template=TemplateType.hy_v3_preview),
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ModelGroup([
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Model('Tencent-Hunyuan/Hy3', 'tencent/Hy3'),
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Model('Tencent-Hunyuan/Hy3-FP8', 'tencent/Hy3-FP8'),
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],
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template=TemplateType.hy_v3),
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],
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requires=['transformers>=5.6.0'],
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architectures=['HYV3ForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.gpt_oss, [
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ModelGroup([
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Model('openai-mirror/gpt-oss-20b', 'openai/gpt-oss-20b'),
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Model('openai-mirror/gpt-oss-120b', 'openai/gpt-oss-120b'),
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])
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],
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template=TemplateType.gpt_oss,
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ignore_patterns=['metal/', 'original/'],
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architectures=['GptOssForCausalLM'],
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requires=['transformers>=4.55']))
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register_model(
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ModelMeta(
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LLMModelType.longchat,
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[
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ModelGroup([
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Model('meituan-longcat/LongCat-Flash-Chat', 'meituan-longcat/LongCat-Flash-Chat'),
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Model('meituan-longcat/LongCat-Flash-Chat-FP8', 'meituan-longcat/LongCat-Flash-Chat-FP8'),
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])
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],
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template=TemplateType.longchat,
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architectures=['LongcatFlashForCausalLM'],
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requires=['transformers>=4.54,<4.56'],
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))
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register_model(
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ModelMeta(
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LLMModelType.bailing_moe,
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[
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ModelGroup([
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Model('inclusionAI/Ling-mini-2.0', 'inclusionAI/Ling-mini-2.0'),
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Model('inclusionAI/Ling-mini-base-2.0', 'inclusionAI/Ling-mini-base-2.0'),
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Model('inclusionAI/Ling-1T', 'inclusionAI/Ling-1T'),
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],
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template=TemplateType.ling2),
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ModelGroup([
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Model('inclusionAI/Ring-mini-2.0', 'inclusionAI/Ring-mini-2.0'),
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], template=TemplateType.ring2)
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],
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architectures=['BailingMoeV2ForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.bailing_hybrid,
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[
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ModelGroup([
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Model('inclusionAI/Ling-2.5-1T', 'inclusionAI/Ling-2.5-1T'),
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Model('inclusionAI/Ling-2.6-1T', 'inclusionAI/Ling-2.6-1T'),
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Model('inclusionAI/Ling-2.6-flash', 'inclusionAI/Ling-2.6-flash'),
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],
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template=TemplateType.ling2),
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ModelGroup([
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Model('inclusionAI/Ring-2.5-1T', 'inclusionAI/Ring-2.5-1T'),
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Model('inclusionAI/Ring-2.6-1T', 'inclusionAI/Ring-2.6-1T'),
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],
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template=TemplateType.ring2_5),
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],
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architectures=['BailingMoeV2_5ForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.iquestcoder,
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[
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ModelGroup([
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Model('IQuestLab/IQuest-Coder-V1-40B-Base-Stage1', 'IQuestLab/IQuest-Coder-V1-40B-Base-Stage1'),
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Model('IQuestLab/IQuest-Coder-V1-40B-Base', 'IQuestLab/IQuest-Coder-V1-40B-Base'),
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Model('IQuestLab/IQuest-Coder-V1-40B-Instruct', 'IQuestLab/IQuest-Coder-V1-40B-Instruct'),
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])
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],
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template=TemplateType.iquestcoder,
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requires=['transformers==4.52.4'],
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architectures=['IQuestCoderForCausalLM'],
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))
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register_model(
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ModelMeta(
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LLMModelType.youtu_llm,
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[
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ModelGroup([
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Model('Tencent-YouTu-Research/Youtu-LLM-2B', 'tencent/Youtu-LLM-2B'),
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Model('Tencent-YouTu-Research/Youtu-LLM-2B-Base', 'tencent/Youtu-LLM-2B-Base'),
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])
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],
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template=TemplateType.youtu_llm,
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architectures=['YoutuForCausalLM'],
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requires=['transformers>=4.56'],
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))
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register_model(
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ModelMeta(
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LLMModelType.olmoe,
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[
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ModelGroup([
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Model('allenai/OLMoE-1B-7B-0125', 'allenai/OLMoE-1B-7B-0125'),
|
|
Model('allenai/OLMoE-1B-7B-0125-Instruct', 'allenai/OLMoE-1B-7B-0125-Instruct'),
|
|
],
|
|
template=TemplateType.olmoe),
|
|
ModelGroup([
|
|
Model('allenai/OLMoE-1B-7B-0924', 'allenai/OLMoE-1B-7B-0924'),
|
|
Model('allenai/OLMoE-1B-7B-0924-Instruct', 'allenai/OLMoE-1B-7B-0924-Instruct'),
|
|
Model('allenai/OLMoE-1B-7B-0924-SFT', 'allenai/OLMoE-1B-7B-0924-SFT'),
|
|
],
|
|
template=TemplateType.olmoe_0924)
|
|
],
|
|
architectures=['OlmoeForCausalLM'],
|
|
))
|