# SPDX-License-Identifier: Apache-2.0 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project from collections.abc import Mapping, Set from dataclasses import dataclass, field from typing import Any, Literal, Optional import pytest from packaging.version import Version from transformers import __version__ as TRANSFORMERS_VERSION from vllm.config import TokenizerMode @dataclass(frozen=True) class _HfExamplesInfo: default: str """The default model to use for testing this architecture.""" extras: Mapping[str, str] = field(default_factory=dict) """Extra models to use for testing this architecture.""" tokenizer: Optional[str] = None """Set the tokenizer to load for this architecture.""" tokenizer_mode: TokenizerMode = "auto" """Set the tokenizer type for this architecture.""" speculative_model: Optional[str] = None """ The default model to use for testing this architecture, which is only used for speculative decoding. """ min_transformers_version: Optional[str] = None """ The minimum version of HF Transformers that is required to run this model. """ max_transformers_version: Optional[str] = None """ The maximum version of HF Transformers that this model runs on. """ transformers_version_reason: Optional[str] = None """ The reason for the minimum/maximum version requirement. """ is_available_online: bool = True """ Set this to ``False`` if the name of this architecture no longer exists on the HF repo. To maintain backwards compatibility, we have not removed them from the main model registry, so without this flag the registry tests will fail. """ trust_remote_code: bool = False """The ``trust_remote_code`` level required to load the model.""" v0_only: bool = False """The model is only available with the vLLM V0 engine.""" hf_overrides: dict[str, Any] = field(default_factory=dict) """The ``hf_overrides`` required to load the model.""" max_model_len: Optional[int] = None """ The maximum model length to use for this model. Some models default to a length that is too large to fit into memory in CI. """ revision: Optional[str] = None """ The specific revision (commit hash, tag, or branch) to use for the model. If not specified, the default revision will be used. """ def check_transformers_version( self, *, on_fail: Literal["error", "skip", "return"], check_min_version: bool = True, check_max_version: bool = True, ) -> Optional[str]: """ If the installed transformers version does not meet the requirements, perform the given action. """ if (self.min_transformers_version is None and self.max_transformers_version is None): return None current_version = TRANSFORMERS_VERSION cur_base_version = Version(current_version).base_version min_version = self.min_transformers_version max_version = self.max_transformers_version msg = f"`transformers=={current_version}` installed, but `transformers" # Only check the base version for the min/max version, otherwise preview # models cannot be run because `x.yy.0.dev0`<`x.yy.0` if (check_min_version and min_version and Version(cur_base_version) < Version(min_version)): msg += f">={min_version}` is required to run this model." elif (check_max_version and max_version and Version(cur_base_version) > Version(max_version)): msg += f"<={max_version}` is required to run this model." else: return None if self.transformers_version_reason: msg += f" Reason: {self.transformers_version_reason}" if on_fail == "error": raise RuntimeError(msg) elif on_fail == "skip": pytest.skip(msg) return msg def check_available_online( self, *, on_fail: Literal["error", "skip"], ) -> None: """ If the model is not available online, perform the given action. """ if not self.is_available_online: msg = "Model is not available online" if on_fail == "error": raise RuntimeError(msg) else: pytest.skip(msg) # yapf: disable _TEXT_GENERATION_EXAMPLE_MODELS = { # [Decoder-only] "AquilaModel": _HfExamplesInfo("BAAI/AquilaChat-7B", trust_remote_code=True), "AquilaForCausalLM": _HfExamplesInfo("BAAI/AquilaChat2-7B", trust_remote_code=True), "ArceeForCausalLM": _HfExamplesInfo("arcee-ai/AFM-4.5B-Base"), "ArcticForCausalLM": _HfExamplesInfo("Snowflake/snowflake-arctic-instruct", trust_remote_code=True), "BaiChuanForCausalLM": _HfExamplesInfo("baichuan-inc/Baichuan-7B", trust_remote_code=True), "BaichuanForCausalLM": _HfExamplesInfo("baichuan-inc/Baichuan2-7B-chat", trust_remote_code=True), "BailingMoeForCausalLM": _HfExamplesInfo("inclusionAI/Ling-lite-1.5", trust_remote_code=True), "BambaForCausalLM": _HfExamplesInfo("ibm-ai-platform/Bamba-9B-v1", min_transformers_version="4.56.0", extras={"tiny": "hmellor/tiny-random-BambaForCausalLM"}), # noqa: E501 "BloomForCausalLM": _HfExamplesInfo("bigscience/bloom-560m", {"1b": "bigscience/bloomz-1b1"}), "ChatGLMModel": _HfExamplesInfo("zai-org/chatglm3-6b", trust_remote_code=True, max_transformers_version="4.48"), "ChatGLMForConditionalGeneration": _HfExamplesInfo("thu-coai/ShieldLM-6B-chatglm3", # noqa: E501 trust_remote_code=True), "CohereForCausalLM": _HfExamplesInfo("CohereForAI/c4ai-command-r-v01", trust_remote_code=True), "Cohere2ForCausalLM": _HfExamplesInfo("CohereForAI/c4ai-command-r7b-12-2024", # noqa: E501 trust_remote_code=True), "DbrxForCausalLM": _HfExamplesInfo("databricks/dbrx-instruct"), "DeciLMForCausalLM": _HfExamplesInfo("nvidia/Llama-3_3-Nemotron-Super-49B-v1", # noqa: E501 trust_remote_code=True), "DeepseekForCausalLM": _HfExamplesInfo("deepseek-ai/deepseek-llm-7b-chat"), "DeepseekV2ForCausalLM": _HfExamplesInfo("deepseek-ai/DeepSeek-V2-Lite-Chat", # noqa: E501 trust_remote_code=True), "DeepseekV3ForCausalLM": _HfExamplesInfo("deepseek-ai/DeepSeek-V3", # noqa: E501 trust_remote_code=True), "Ernie4_5ForCausalLM": _HfExamplesInfo("baidu/ERNIE-4.5-0.3B-PT", min_transformers_version="4.54"), "Ernie4_5_MoeForCausalLM": _HfExamplesInfo("baidu/ERNIE-4.5-21B-A3B-PT", min_transformers_version="4.54"), "ExaoneForCausalLM": _HfExamplesInfo("LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct", trust_remote_code=True), "Exaone4ForCausalLM": _HfExamplesInfo("LGAI-EXAONE/EXAONE-4.0-32B", min_transformers_version="4.54"), "Fairseq2LlamaForCausalLM": _HfExamplesInfo("mgleize/fairseq2-dummy-Llama-3.2-1B"), # noqa: E501 "FalconForCausalLM": _HfExamplesInfo("tiiuae/falcon-7b"), "FalconH1ForCausalLM":_HfExamplesInfo("tiiuae/Falcon-H1-0.5B-Base"), "GemmaForCausalLM": _HfExamplesInfo("google/gemma-1.1-2b-it"), "Gemma2ForCausalLM": _HfExamplesInfo("google/gemma-2-9b"), "Gemma3ForCausalLM": _HfExamplesInfo("google/gemma-3-1b-it"), "Gemma3nForCausalLM": _HfExamplesInfo("google/gemma-3n-E2B-it", min_transformers_version="4.53"), "GlmForCausalLM": _HfExamplesInfo("zai-org/glm-4-9b-chat-hf"), "Glm4ForCausalLM": _HfExamplesInfo("zai-org/GLM-4-9B-0414"), "Glm4MoeForCausalLM": _HfExamplesInfo("zai-org/GLM-4.5", min_transformers_version="4.54"), # noqa: E501 "GPT2LMHeadModel": _HfExamplesInfo("openai-community/gpt2", {"alias": "gpt2"}), "GPTBigCodeForCausalLM": _HfExamplesInfo("bigcode/starcoder", extras={"tiny": "bigcode/tiny_starcoder_py"}, # noqa: E501 min_transformers_version="4.55.1", transformers_version_reason="HF model broken in 4.55.0"), # noqa: E501 "GPTJForCausalLM": _HfExamplesInfo("Milos/slovak-gpt-j-405M", {"6b": "EleutherAI/gpt-j-6b"}), "GPTNeoXForCausalLM": _HfExamplesInfo("EleutherAI/pythia-70m", {"1b": "EleutherAI/pythia-1.4b"}), "GptOssForCausalLM": _HfExamplesInfo("lmsys/gpt-oss-20b-bf16"), "GraniteForCausalLM": _HfExamplesInfo("ibm/PowerLM-3b"), "GraniteMoeForCausalLM": _HfExamplesInfo("ibm/PowerMoE-3b"), "GraniteMoeHybridForCausalLM": _HfExamplesInfo("ibm-granite/granite-4.0-tiny-preview"), # noqa: E501 "GraniteMoeSharedForCausalLM": _HfExamplesInfo("ibm-research/moe-7b-1b-active-shared-experts"), # noqa: E501 "Grok1ModelForCausalLM": _HfExamplesInfo("hpcai-tech/grok-1", trust_remote_code=True), "HunYuanMoEV1ForCausalLM": _HfExamplesInfo("tencent/Hunyuan-A13B-Instruct", trust_remote_code=True), # TODO: Remove is_available_online once their config.json is fixed "HunYuanDenseV1ForCausalLM":_HfExamplesInfo("tencent/Hunyuan-7B-Instruct-0124", trust_remote_code=True, is_available_online=False), "HCXVisionForCausalLM": _HfExamplesInfo( "naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B", trust_remote_code=True), "InternLMForCausalLM": _HfExamplesInfo("internlm/internlm-chat-7b", trust_remote_code=True), "InternLM2ForCausalLM": _HfExamplesInfo("internlm/internlm2-chat-7b", trust_remote_code=True), "InternLM2VEForCausalLM": _HfExamplesInfo("OpenGVLab/Mono-InternVL-2B", trust_remote_code=True), "InternLM3ForCausalLM": _HfExamplesInfo("internlm/internlm3-8b-instruct", trust_remote_code=True), "JAISLMHeadModel": _HfExamplesInfo("inceptionai/jais-13b-chat"), "JambaForCausalLM": _HfExamplesInfo("ai21labs/AI21-Jamba-1.5-Mini", min_transformers_version="4.56.0", extras={ "tiny": "ai21labs/Jamba-tiny-dev", "random": "ai21labs/Jamba-tiny-random", # noqa: E501 }), "LlamaForCausalLM": _HfExamplesInfo("meta-llama/Llama-3.2-1B-Instruct", extras={"guard": "meta-llama/Llama-Guard-3-1B", # noqa: E501 "hermes": "NousResearch/Hermes-3-Llama-3.1-8B", # noqa: E501 "fp8": "RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8"}), # noqa: E501 "LLaMAForCausalLM": _HfExamplesInfo("decapoda-research/llama-7b-hf", is_available_online=False), "Llama4ForCausalLM": _HfExamplesInfo("meta-llama/Llama-4-Scout-17B-16E-Instruct", # noqa: E501 is_available_online=False), "MambaForCausalLM": _HfExamplesInfo("state-spaces/mamba-130m-hf"), "Mamba2ForCausalLM": _HfExamplesInfo("mistralai/Mamba-Codestral-7B-v0.1"), "FalconMambaForCausalLM": _HfExamplesInfo("tiiuae/falcon-mamba-7b-instruct"), # noqa: E501 "MiniCPMForCausalLM": _HfExamplesInfo("openbmb/MiniCPM-2B-sft-bf16", trust_remote_code=True), "MiniCPM3ForCausalLM": _HfExamplesInfo("openbmb/MiniCPM3-4B", trust_remote_code=True), "MiniMaxForCausalLM": _HfExamplesInfo("MiniMaxAI/MiniMax-Text-01-hf"), "MiniMaxText01ForCausalLM": _HfExamplesInfo("MiniMaxAI/MiniMax-Text-01", trust_remote_code=True, revision="a59aa9cbc53b9fb8742ca4e9e1531b9802b6fdc3"), # noqa: E501 "MiniMaxM1ForCausalLM": _HfExamplesInfo("MiniMaxAI/MiniMax-M1-40k", trust_remote_code=True), "MistralForCausalLM": _HfExamplesInfo("mistralai/Mistral-7B-Instruct-v0.1"), "MixtralForCausalLM": _HfExamplesInfo("mistralai/Mixtral-8x7B-Instruct-v0.1", # noqa: E501 {"tiny": "TitanML/tiny-mixtral"}), # noqa: E501 "QuantMixtralForCausalLM": _HfExamplesInfo("mistral-community/Mixtral-8x22B-v0.1-AWQ"), # noqa: E501 "MptForCausalLM": _HfExamplesInfo("mpt", is_available_online=False), "MPTForCausalLM": _HfExamplesInfo("mosaicml/mpt-7b"), "NemotronForCausalLM": _HfExamplesInfo("nvidia/Minitron-8B-Base"), "NemotronHForCausalLM": _HfExamplesInfo("nvidia/Nemotron-H-8B-Base-8K", trust_remote_code=True), "OlmoForCausalLM": _HfExamplesInfo("allenai/OLMo-1B-hf"), "Olmo2ForCausalLM": _HfExamplesInfo("allenai/OLMo-2-0425-1B"), "OlmoeForCausalLM": _HfExamplesInfo("allenai/OLMoE-1B-7B-0924-Instruct"), "OPTForCausalLM": _HfExamplesInfo("facebook/opt-125m", {"1b": "facebook/opt-iml-max-1.3b"}), "OrionForCausalLM": _HfExamplesInfo("OrionStarAI/Orion-14B-Chat", trust_remote_code=True), "PersimmonForCausalLM": _HfExamplesInfo("adept/persimmon-8b-chat"), "PhiForCausalLM": _HfExamplesInfo("microsoft/phi-2"), "Phi3ForCausalLM": _HfExamplesInfo("microsoft/Phi-3-mini-4k-instruct"), "Phi4FlashForCausalLM": _HfExamplesInfo("microsoft/Phi-4-mini-flash-reasoning", # noqa: E501 trust_remote_code=True, v0_only=True, max_model_len=10240), "PhiMoEForCausalLM": _HfExamplesInfo("microsoft/Phi-3.5-MoE-instruct", trust_remote_code=True), "Plamo2ForCausalLM": _HfExamplesInfo("pfnet/plamo-2-1b", max_transformers_version="4.53", transformers_version_reason="vLLM impl inherits PreTrainedModel and clashes with get_input_embeddings", # noqa: E501 trust_remote_code=True), "QWenLMHeadModel": _HfExamplesInfo("Qwen/Qwen-7B-Chat", max_transformers_version="4.53", transformers_version_reason="HF model uses remote code that is not compatible with latest Transformers", # noqa: E501 trust_remote_code=True), "Qwen2ForCausalLM": _HfExamplesInfo("Qwen/Qwen2-0.5B-Instruct", extras={"2.5": "Qwen/Qwen2.5-0.5B-Instruct"}), # noqa: E501 "Qwen2MoeForCausalLM": _HfExamplesInfo("Qwen/Qwen1.5-MoE-A2.7B-Chat"), "Qwen3ForCausalLM": _HfExamplesInfo("Qwen/Qwen3-8B"), "Qwen3MoeForCausalLM": _HfExamplesInfo("Qwen/Qwen3-30B-A3B"), "RWForCausalLM": _HfExamplesInfo("tiiuae/falcon-40b"), "SmolLM3ForCausalLM": _HfExamplesInfo("HuggingFaceTB/SmolLM3-3B"), "StableLMEpochForCausalLM": _HfExamplesInfo("stabilityai/stablelm-zephyr-3b"), # noqa: E501 "StableLmForCausalLM": _HfExamplesInfo("stabilityai/stablelm-3b-4e1t"), "Starcoder2ForCausalLM": _HfExamplesInfo("bigcode/starcoder2-3b"), "Step3TextForCausalLM": _HfExamplesInfo("stepfun-ai/step3", trust_remote_code=True, is_available_online=False), "SolarForCausalLM": _HfExamplesInfo("upstage/solar-pro-preview-instruct", trust_remote_code=True), "TeleChat2ForCausalLM": _HfExamplesInfo("Tele-AI/TeleChat2-3B", trust_remote_code=True), "TeleFLMForCausalLM": _HfExamplesInfo("CofeAI/FLM-2-52B-Instruct-2407", trust_remote_code=True), "XverseForCausalLM": _HfExamplesInfo("xverse/XVERSE-7B-Chat", tokenizer="meta-llama/Llama-2-7b", trust_remote_code=True), "Zamba2ForCausalLM": _HfExamplesInfo("Zyphra/Zamba2-7B-instruct"), "MiMoForCausalLM": _HfExamplesInfo("XiaomiMiMo/MiMo-7B-RL", trust_remote_code=True), "Dots1ForCausalLM": _HfExamplesInfo("rednote-hilab/dots.llm1.inst"), # [Encoder-decoder] "BartModel": _HfExamplesInfo("facebook/bart-base"), "BartForConditionalGeneration": _HfExamplesInfo("facebook/bart-large-cnn"), "MBartForConditionalGeneration": _HfExamplesInfo("facebook/mbart-large-en-ro", # noqa: E501 hf_overrides={"architectures": ["MBartForConditionalGeneration"]}), # noqa: E501 } _EMBEDDING_EXAMPLE_MODELS = { # [Text-only] "BertModel": _HfExamplesInfo("BAAI/bge-base-en-v1.5", v0_only=True), "Gemma2Model": _HfExamplesInfo("BAAI/bge-multilingual-gemma2", v0_only=True), # noqa: E501 "GritLM": _HfExamplesInfo("parasail-ai/GritLM-7B-vllm"), "GteModel": _HfExamplesInfo("Snowflake/snowflake-arctic-embed-m-v2.0", trust_remote_code=True), "GteNewModel": _HfExamplesInfo("Alibaba-NLP/gte-base-en-v1.5", trust_remote_code=True, hf_overrides={"architectures": ["GteNewModel"]}), # noqa: E501 "InternLM2ForRewardModel": _HfExamplesInfo("internlm/internlm2-1_8b-reward", trust_remote_code=True), "JambaForSequenceClassification": _HfExamplesInfo("ai21labs/Jamba-tiny-reward-dev"), # noqa: E501 "LlamaModel": _HfExamplesInfo("llama", is_available_online=False), "MistralModel": _HfExamplesInfo("intfloat/e5-mistral-7b-instruct"), "ModernBertModel": _HfExamplesInfo("Alibaba-NLP/gte-modernbert-base", trust_remote_code=True, v0_only=True), "NomicBertModel": _HfExamplesInfo("nomic-ai/nomic-embed-text-v2-moe", trust_remote_code=True, v0_only=True), # noqa: E501 "Qwen2Model": _HfExamplesInfo("ssmits/Qwen2-7B-Instruct-embed-base"), "Qwen2ForRewardModel": _HfExamplesInfo("Qwen/Qwen2.5-Math-RM-72B", max_transformers_version="4.53", transformers_version_reason="HF model uses remote code that is not compatible with latest Transformers"), # noqa: E501 "Qwen2ForProcessRewardModel": _HfExamplesInfo("Qwen/Qwen2.5-Math-PRM-7B", max_transformers_version="4.53", transformers_version_reason="HF model uses remote code that is not compatible with latest Transformers"), # noqa: E501 "RobertaModel": _HfExamplesInfo("sentence-transformers/stsb-roberta-base-v2", v0_only=True), # noqa: E501 "RobertaForMaskedLM": _HfExamplesInfo("sentence-transformers/all-roberta-large-v1", v0_only=True), # noqa: E501 "XLMRobertaModel": _HfExamplesInfo("intfloat/multilingual-e5-small", v0_only=True), # noqa: E501 # [Multimodal] "LlavaNextForConditionalGeneration": _HfExamplesInfo("royokong/e5-v"), "Phi3VForCausalLM": _HfExamplesInfo("TIGER-Lab/VLM2Vec-Full", trust_remote_code=True), "Qwen2VLForConditionalGeneration": _HfExamplesInfo("MrLight/dse-qwen2-2b-mrl-v1"), # noqa: E501 "PrithviGeoSpatialMAE": _HfExamplesInfo("ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11", # noqa: E501 is_available_online=False), # noqa: E501 } _SEQUENCE_CLASSIFICATION_EXAMPLE_MODELS = { # [Decoder-only] "GPT2ForSequenceClassification": _HfExamplesInfo("nie3e/sentiment-polish-gpt2-small"), # noqa: E501 # [Cross-encoder] "BertForSequenceClassification": _HfExamplesInfo("cross-encoder/ms-marco-MiniLM-L-6-v2", v0_only=True), # noqa: E501 "ModernBertForSequenceClassification": _HfExamplesInfo("Alibaba-NLP/gte-reranker-modernbert-base", v0_only=True), # noqa: E501 "RobertaForSequenceClassification": _HfExamplesInfo("cross-encoder/quora-roberta-base", v0_only=True), # noqa: E501 "XLMRobertaForSequenceClassification": _HfExamplesInfo("BAAI/bge-reranker-v2-m3", v0_only=True), # noqa: E501 } _AUTOMATIC_CONVERTED_MODELS = { # Use as_seq_cls_model for automatic conversion "GemmaForSequenceClassification": _HfExamplesInfo("BAAI/bge-reranker-v2-gemma", # noqa: E501 v0_only=True, hf_overrides={"architectures": ["GemmaForSequenceClassification"], # noqa: E501 "classifier_from_token": ["Yes"], # noqa: E501 "method": "no_post_processing"}), # noqa: E501 "LlamaForSequenceClassification": _HfExamplesInfo("Skywork/Skywork-Reward-V2-Llama-3.2-1B"), # noqa: E501 "Qwen2ForSequenceClassification": _HfExamplesInfo("jason9693/Qwen2.5-1.5B-apeach"), # noqa: E501 "Qwen3ForSequenceClassification": _HfExamplesInfo("tomaarsen/Qwen3-Reranker-0.6B-seq-cls"), # noqa: E501 } _MULTIMODAL_EXAMPLE_MODELS = { # [Decoder-only] "AriaForConditionalGeneration": _HfExamplesInfo("rhymes-ai/Aria"), "AyaVisionForConditionalGeneration": _HfExamplesInfo("CohereForAI/aya-vision-8b"), # noqa: E501 "Blip2ForConditionalGeneration": _HfExamplesInfo("Salesforce/blip2-opt-2.7b", # noqa: E501 extras={"6b": "Salesforce/blip2-opt-6.7b"}), # noqa: E501 "ChameleonForConditionalGeneration": _HfExamplesInfo("facebook/chameleon-7b"), # noqa: E501 "Cohere2VisionForConditionalGeneration": _HfExamplesInfo("CohereLabs/command-a-vision-07-2025"), # noqa: E501 "DeepseekVLV2ForCausalLM": _HfExamplesInfo("deepseek-ai/deepseek-vl2-tiny", # noqa: E501 extras={"fork": "Isotr0py/deepseek-vl2-tiny"}, # noqa: E501 max_transformers_version="4.48", # noqa: E501 transformers_version_reason="HF model is not compatible.", # noqa: E501 hf_overrides={"architectures": ["DeepseekVLV2ForCausalLM"]}), # noqa: E501 "Emu3ForConditionalGeneration": _HfExamplesInfo("BAAI/Emu3-Chat-hf"), "FuyuForCausalLM": _HfExamplesInfo("adept/fuyu-8b"), "Gemma3ForConditionalGeneration": _HfExamplesInfo("google/gemma-3-4b-it"), "Gemma3nForConditionalGeneration": _HfExamplesInfo("google/gemma-3n-E2B-it", # noqa: E501 min_transformers_version="4.53"), "GraniteSpeechForConditionalGeneration": _HfExamplesInfo("ibm-granite/granite-speech-3.3-2b"), # noqa: E501 "GLM4VForCausalLM": _HfExamplesInfo("zai-org/glm-4v-9b", trust_remote_code=True, hf_overrides={"architectures": ["GLM4VForCausalLM"]}), # noqa: E501 "Glm4vForConditionalGeneration": _HfExamplesInfo("zai-org/GLM-4.1V-9B-Thinking"), # noqa: E501 "Glm4vMoeForConditionalGeneration": _HfExamplesInfo("zai-org/GLM-4.5V", is_available_online=False), # noqa: E501 "H2OVLChatModel": _HfExamplesInfo("h2oai/h2ovl-mississippi-800m", trust_remote_code=True, extras={"2b": "h2oai/h2ovl-mississippi-2b"}, # noqa: E501 max_transformers_version="4.48", # noqa: E501 transformers_version_reason="HF model is not compatible."), # noqa: E501 "Idefics3ForConditionalGeneration": _HfExamplesInfo("HuggingFaceM4/Idefics3-8B-Llama3", # noqa: E501 {"tiny": "HuggingFaceTB/SmolVLM-256M-Instruct"}, # noqa: E501 min_transformers_version="4.55.1", transformers_version_reason="HF model broken in 4.55.0"), # noqa: E501 "InternVLChatModel": _HfExamplesInfo("OpenGVLab/InternVL2-1B", extras={"2B": "OpenGVLab/InternVL2-2B", "3.0": "OpenGVLab/InternVL3-1B"}, # noqa: E501 trust_remote_code=True), "InternS1ForConditionalGeneration": _HfExamplesInfo("internlm/Intern-S1", trust_remote_code=True), "KeyeForConditionalGeneration": _HfExamplesInfo("Kwai-Keye/Keye-VL-8B-Preview", # noqa: E501 trust_remote_code=True), "KimiVLForConditionalGeneration": _HfExamplesInfo("moonshotai/Kimi-VL-A3B-Instruct", # noqa: E501 extras={"thinking": "moonshotai/Kimi-VL-A3B-Thinking"}, # noqa: E501 trust_remote_code=True), "Llama4ForConditionalGeneration": _HfExamplesInfo("meta-llama/Llama-4-Scout-17B-16E-Instruct", # noqa: E501 max_model_len=10240, extras={"llama-guard-4": "meta-llama/Llama-Guard-4-12B"}, # noqa: E501 ), "LlavaForConditionalGeneration": _HfExamplesInfo("llava-hf/llava-1.5-7b-hf", extras={"mistral": "mistral-community/pixtral-12b", # noqa: E501 "mistral-fp8": "nm-testing/pixtral-12b-FP8-dynamic"}), # noqa: E501 "LlavaNextForConditionalGeneration": _HfExamplesInfo("llava-hf/llava-v1.6-mistral-7b-hf"), # noqa: E501 "LlavaNextVideoForConditionalGeneration": _HfExamplesInfo("llava-hf/LLaVA-NeXT-Video-7B-hf"), # noqa: E501 "LlavaOnevisionForConditionalGeneration": _HfExamplesInfo("llava-hf/llava-onevision-qwen2-0.5b-ov-hf"), # noqa: E501 "MantisForConditionalGeneration": _HfExamplesInfo("TIGER-Lab/Mantis-8B-siglip-llama3", # noqa: E501 max_transformers_version="4.48", # noqa: E501 transformers_version_reason="HF model is not compatible.", # noqa: E501 hf_overrides={"architectures": ["MantisForConditionalGeneration"]}), # noqa: E501 "MiniCPMO": _HfExamplesInfo("openbmb/MiniCPM-o-2_6", trust_remote_code=True), "MiniCPMV": _HfExamplesInfo("openbmb/MiniCPM-Llama3-V-2_5", extras={"2.6": "openbmb/MiniCPM-V-2_6", "4.0": "openbmb/MiniCPM-V-4"}, # noqa: E501 trust_remote_code=True), "MiniMaxVL01ForConditionalGeneration": _HfExamplesInfo("MiniMaxAI/MiniMax-VL-01", # noqa: E501 trust_remote_code=True, v0_only=True), "Mistral3ForConditionalGeneration": _HfExamplesInfo("mistralai/Mistral-Small-3.1-24B-Instruct-2503", # noqa: E501 extras={"fp8": "nm-testing/Mistral-Small-3.1-24B-Instruct-2503-FP8-dynamic"}), # noqa: E501 "MolmoForCausalLM": _HfExamplesInfo("allenai/Molmo-7B-D-0924", max_transformers_version="4.48", transformers_version_reason="Incorrectly-detected `tensorflow` import.", # noqa: E501 extras={"olmo": "allenai/Molmo-7B-O-0924"}, # noqa: E501 trust_remote_code=True), "NVLM_D": _HfExamplesInfo("nvidia/NVLM-D-72B", trust_remote_code=True), "Llama_Nemotron_Nano_VL" : _HfExamplesInfo("nvidia/Llama-3.1-Nemotron-Nano-VL-8B-V1", # noqa: E501 trust_remote_code=True), "Ovis": _HfExamplesInfo("AIDC-AI/Ovis2-1B", trust_remote_code=True, max_transformers_version="4.53", transformers_version_reason="HF model is not compatible", # noqa: E501 extras={"1.6-llama": "AIDC-AI/Ovis1.6-Llama3.2-3B", "1.6-gemma": "AIDC-AI/Ovis1.6-Gemma2-9B"}), # noqa: E501 "PaliGemmaForConditionalGeneration": _HfExamplesInfo("google/paligemma-3b-mix-224", # noqa: E501 extras={"v2": "google/paligemma2-3b-ft-docci-448"}), # noqa: E501 "Phi3VForCausalLM": _HfExamplesInfo("microsoft/Phi-3-vision-128k-instruct", trust_remote_code=True, max_transformers_version="4.48", transformers_version_reason="Use of deprecated imports which have been removed.", # noqa: E501 extras={"phi3.5": "microsoft/Phi-3.5-vision-instruct"}), # noqa: E501 "Phi4MMForCausalLM": _HfExamplesInfo("microsoft/Phi-4-multimodal-instruct", trust_remote_code=True), "Phi4MultimodalForCausalLM": _HfExamplesInfo("microsoft/Phi-4-multimodal-instruct", # noqa: E501 revision="refs/pr/70"), "PixtralForConditionalGeneration": _HfExamplesInfo("mistralai/Pixtral-12B-2409", # noqa: E501 tokenizer_mode="mistral"), "QwenVLForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen-VL", extras={"chat": "Qwen/Qwen-VL-Chat"}, # noqa: E501 trust_remote_code=True, hf_overrides={"architectures": ["QwenVLForConditionalGeneration"]}), # noqa: E501 "Qwen2AudioForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen2-Audio-7B-Instruct"), # noqa: E501 "Qwen2VLForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen2-VL-2B-Instruct"), # noqa: E501 "Qwen2_5_VLForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen2.5-VL-3B-Instruct", # noqa: E501 max_model_len=4096), "Qwen2_5OmniModel": _HfExamplesInfo("Qwen/Qwen2.5-Omni-3B"), "Qwen2_5OmniForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen2.5-Omni-7B-AWQ"), # noqa: E501 "SkyworkR1VChatModel": _HfExamplesInfo("Skywork/Skywork-R1V-38B", trust_remote_code=True), "SmolVLMForConditionalGeneration": _HfExamplesInfo("HuggingFaceTB/SmolVLM2-2.2B-Instruct", # noqa: E501 min_transformers_version="4.55.1", transformers_version_reason="HF model broken in 4.55.0"), # noqa: E501 "Step3VLForConditionalGeneration": _HfExamplesInfo("stepfun-ai/step3", trust_remote_code=True, is_available_online=False), "UltravoxModel": _HfExamplesInfo("fixie-ai/ultravox-v0_5-llama-3_2-1b", # noqa: E501 trust_remote_code=True), "TarsierForConditionalGeneration": _HfExamplesInfo("omni-research/Tarsier-7b"), # noqa: E501 "Tarsier2ForConditionalGeneration": _HfExamplesInfo("omni-research/Tarsier2-Recap-7b", # noqa: E501 hf_overrides={"architectures": ["Tarsier2ForConditionalGeneration"]}), # noqa: E501 "VoxtralForConditionalGeneration": _HfExamplesInfo( "mistralai/Voxtral-Mini-3B-2507", min_transformers_version="4.54", # disable this temporarily until we support HF format is_available_online=False, ), # [Encoder-decoder] # Florence-2 uses BartFastTokenizer which can't be loaded from AutoTokenizer # Therefore, we borrow the BartTokenizer from the original Bart model "Florence2ForConditionalGeneration": _HfExamplesInfo("microsoft/Florence-2-base", # noqa: E501 tokenizer="Isotr0py/Florence-2-tokenizer", # noqa: E501 trust_remote_code=True), # noqa: E501 "MllamaForConditionalGeneration": _HfExamplesInfo("meta-llama/Llama-3.2-11B-Vision-Instruct"), # noqa: E501 "WhisperForConditionalGeneration": _HfExamplesInfo("openai/whisper-large-v3"), # noqa: E501 # [Cross-encoder] "JinaVLForRanking": _HfExamplesInfo("jinaai/jina-reranker-m0"), # noqa: E501 } _SPECULATIVE_DECODING_EXAMPLE_MODELS = { "MedusaModel": _HfExamplesInfo("JackFram/llama-68m", speculative_model="abhigoyal/vllm-medusa-llama-68m-random"), # noqa: E501 # Temporarily disabled. # TODO(woosuk): Re-enable this once the MLP Speculator is supported in V1. # "MLPSpeculatorPreTrainedModel": _HfExamplesInfo("JackFram/llama-160m", # speculative_model="ibm-ai-platform/llama-160m-accelerator"), # noqa: E501 "DeepSeekMTPModel": _HfExamplesInfo("luccafong/deepseek_mtp_main_random", speculative_model="luccafong/deepseek_mtp_draft_random", # noqa: E501 trust_remote_code=True), "EagleLlamaForCausalLM": _HfExamplesInfo("yuhuili/EAGLE-LLaMA3-Instruct-8B", trust_remote_code=True, speculative_model="yuhuili/EAGLE-LLaMA3-Instruct-8B", tokenizer="meta-llama/Meta-Llama-3-8B-Instruct"), # noqa: E501 "Eagle3LlamaForCausalLM": _HfExamplesInfo("yuhuili/EAGLE3-LLaMA3.1-Instruct-8B", # noqa: E501 trust_remote_code=True, speculative_model="yuhuili/EAGLE3-LLaMA3.1-Instruct-8B", tokenizer="meta-llama/Llama-3.1-8B-Instruct"), # TODO: Re-enable this once tests/models/test_initialization.py is fixed, see PR #22333 #22611 # noqa: E501 # "LlamaForCausalLMEagle3": _HfExamplesInfo("AngelSlim/Qwen3-8B_eagle3", # noqa: E501 # trust_remote_code=True, # speculative_model="AngelSlim/Qwen3-8B_eagle3", # noqa: E501 # tokenizer="Qwen/Qwen3-8B"), "EagleLlama4ForCausalLM": _HfExamplesInfo( "morgendave/EAGLE-Llama-4-Scout-17B-16E-Instruct", trust_remote_code=True, speculative_model="morgendave/EAGLE-Llama-4-Scout-17B-16E-Instruct", tokenizer="meta-llama/Llama-4-Scout-17B-16E-Instruct"), # noqa: E501 "EagleMiniCPMForCausalLM": _HfExamplesInfo("openbmb/MiniCPM-1B-sft-bf16", trust_remote_code=True, is_available_online=False, speculative_model="openbmb/MiniCPM-2B-sft-bf16", tokenizer="openbmb/MiniCPM-2B-sft-bf16"), "Glm4MoeMTPModel": _HfExamplesInfo("zai-org/GLM-4.5", speculative_model="zai-org/GLM-4.5", min_transformers_version="4.54", is_available_online=False), "MiMoMTPModel": _HfExamplesInfo("XiaomiMiMo/MiMo-7B-RL", trust_remote_code=True, speculative_model="XiaomiMiMo/MiMo-7B-RL") } _TRANSFORMERS_BACKEND_MODELS = { "TransformersModel": _HfExamplesInfo("Qwen/Qwen3-Embedding-0.6B"), "TransformersForCausalLM": _HfExamplesInfo("hmellor/Ilama-3.2-1B", trust_remote_code=True), # noqa: E501 "TransformersForMultimodalLM": _HfExamplesInfo("OpenGVLab/InternVL3-1B-hf"), } _EXAMPLE_MODELS = { **_TEXT_GENERATION_EXAMPLE_MODELS, **_EMBEDDING_EXAMPLE_MODELS, **_SEQUENCE_CLASSIFICATION_EXAMPLE_MODELS, **_MULTIMODAL_EXAMPLE_MODELS, **_SPECULATIVE_DECODING_EXAMPLE_MODELS, **_TRANSFORMERS_BACKEND_MODELS, } class HfExampleModels: def __init__(self, hf_models: Mapping[str, _HfExamplesInfo]) -> None: super().__init__() self.hf_models = hf_models def get_supported_archs(self) -> Set[str]: return self.hf_models.keys() def get_hf_info(self, model_arch: str) -> _HfExamplesInfo: return self.hf_models[model_arch] def find_hf_info(self, model_id: str) -> _HfExamplesInfo: for info in self.hf_models.values(): if info.default == model_id: return info # Fallback to extras for info in self.hf_models.values(): if any(extra == model_id for extra in info.extras.values()): return info raise ValueError(f"No example model defined for {model_id}") HF_EXAMPLE_MODELS = HfExampleModels(_EXAMPLE_MODELS) AUTO_EXAMPLE_MODELS = HfExampleModels(_AUTOMATIC_CONVERTED_MODELS)