# SPDX-License-Identifier: Apache-2.0 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 @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: str = "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.""" hf_overrides: dict[str, Any] = field(default_factory=dict) """The ``hf_overrides`` required to load the model.""" def check_transformers_version( self, *, on_fail: Literal["error", "skip"], ) -> None: """ 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 current_version = TRANSFORMERS_VERSION min_version = self.min_transformers_version max_version = self.max_transformers_version msg = f"`transformers=={current_version}` installed, but `transformers" if min_version and Version(current_version) < Version(min_version): msg += f">={min_version}` is required to run this model." elif max_version and Version(current_version) > Version(max_version): msg += f"<={max_version}` is required to run this model." else: return if self.transformers_version_reason: msg += f" Reason: {self.transformers_version_reason}" if on_fail == "error": raise RuntimeError(msg) else: pytest.skip(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), "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), "BambaForCausalLM": _HfExamplesInfo("ibm-ai-platform/Bamba-9B"), "BloomForCausalLM": _HfExamplesInfo("bigscience/bloomz-1b1"), "ChatGLMModel": _HfExamplesInfo("THUDM/chatglm3-6b", 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), "ExaoneForCausalLM": _HfExamplesInfo("LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct"), # noqa: E501 "Fairseq2LlamaForCausalLM": _HfExamplesInfo("mgleize/fairseq2-dummy-Llama-3.2-1B"), # noqa: E501 "FalconForCausalLM": _HfExamplesInfo("tiiuae/falcon-7b"), "GemmaForCausalLM": _HfExamplesInfo("google/gemma-2b"), "Gemma2ForCausalLM": _HfExamplesInfo("google/gemma-2-9b"), "Gemma3ForCausalLM": _HfExamplesInfo("google/gemma-3-1b-it", min_transformers_version="4.50"), "GlmForCausalLM": _HfExamplesInfo("THUDM/glm-4-9b-chat-hf"), "GPT2LMHeadModel": _HfExamplesInfo("gpt2"), "GPTBigCodeForCausalLM": _HfExamplesInfo("bigcode/starcoder"), "GPTJForCausalLM": _HfExamplesInfo("EleutherAI/gpt-j-6b"), "GPTNeoXForCausalLM": _HfExamplesInfo("EleutherAI/pythia-160m"), "GraniteForCausalLM": _HfExamplesInfo("ibm/PowerLM-3b"), "GraniteMoeForCausalLM": _HfExamplesInfo("ibm/PowerMoE-3b"), "GraniteMoeSharedForCausalLM": _HfExamplesInfo("ibm-research/moe-7b-1b-active-shared-experts", # noqa: E501 min_transformers_version="4.49"), # noqa: E501 "Grok1ModelForCausalLM": _HfExamplesInfo("hpcai-tech/grok-1", 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", extras={"tiny": "ai21labs/Jamba-tiny-dev"}), # noqa: E501 "LlamaForCausalLM": _HfExamplesInfo("meta-llama/Llama-3.2-1B-Instruct"), "LLaMAForCausalLM": _HfExamplesInfo("decapoda-research/llama-7b-hf", is_available_online=False), "MambaForCausalLM": _HfExamplesInfo("state-spaces/mamba-130m-hf"), "Mamba2ForCausalLM": _HfExamplesInfo("mistralai/Mamba-Codestral-7B-v0.1", is_available_online=False), "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), "MistralForCausalLM": _HfExamplesInfo("mistralai/Mistral-7B-Instruct-v0.1"), "MixtralForCausalLM": _HfExamplesInfo("mistralai/Mixtral-8x7B-Instruct-v0.1"), # 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"), "OlmoForCausalLM": _HfExamplesInfo("allenai/OLMo-1B-hf"), "Olmo2ForCausalLM": _HfExamplesInfo("shanearora/OLMo-7B-1124-hf"), "OlmoeForCausalLM": _HfExamplesInfo("allenai/OLMoE-1B-7B-0924-Instruct"), "OPTForCausalLM": _HfExamplesInfo("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"), "Phi3SmallForCausalLM": _HfExamplesInfo("microsoft/Phi-3-small-8k-instruct", trust_remote_code=True), "PhiMoEForCausalLM": _HfExamplesInfo("microsoft/Phi-3.5-MoE-instruct", trust_remote_code=True), "QWenLMHeadModel": _HfExamplesInfo("Qwen/Qwen-7B-Chat", trust_remote_code=True), "Qwen2ForCausalLM": _HfExamplesInfo("Qwen/Qwen2-7B-Instruct", extras={"2.5": "Qwen/Qwen2.5-7B-Instruct"}), # noqa: E501 "Qwen2MoeForCausalLM": _HfExamplesInfo("Qwen/Qwen1.5-MoE-A2.7B-Chat"), "RWForCausalLM": _HfExamplesInfo("tiiuae/falcon-40b", is_available_online=False), "StableLMEpochForCausalLM": _HfExamplesInfo("stabilityai/stablelm-zephyr-3b", # noqa: E501 is_available_online=False), "StableLmForCausalLM": _HfExamplesInfo("stabilityai/stablelm-3b-4e1t"), "Starcoder2ForCausalLM": _HfExamplesInfo("bigcode/starcoder2-3b"), "SolarForCausalLM": _HfExamplesInfo("upstage/solar-pro-preview-instruct"), "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", is_available_online=False, trust_remote_code=True), "Zamba2ForCausalLM": _HfExamplesInfo("Zyphra/Zamba2-7B-instruct", min_transformers_version="4.49"), # [Encoder-decoder] "BartModel": _HfExamplesInfo("facebook/bart-base"), "BartForConditionalGeneration": _HfExamplesInfo("facebook/bart-large-cnn"), } _EMBEDDING_EXAMPLE_MODELS = { # [Text-only] "BertModel": _HfExamplesInfo("BAAI/bge-base-en-v1.5"), "Gemma2Model": _HfExamplesInfo("BAAI/bge-multilingual-gemma2"), "GritLM": _HfExamplesInfo("parasail-ai/GritLM-7B-vllm"), "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"), "Qwen2Model": _HfExamplesInfo("ssmits/Qwen2-7B-Instruct-embed-base"), "Qwen2ForRewardModel": _HfExamplesInfo("Qwen/Qwen2.5-Math-RM-72B"), "Qwen2ForProcessRewardModel": _HfExamplesInfo("Qwen/Qwen2.5-Math-PRM-7B"), "Qwen2ForSequenceClassification": _HfExamplesInfo("jason9693/Qwen2.5-1.5B-apeach"), # noqa: E501 "RobertaModel": _HfExamplesInfo("sentence-transformers/stsb-roberta-base-v2"), # noqa: E501 "RobertaForMaskedLM": _HfExamplesInfo("sentence-transformers/all-roberta-large-v1"), # noqa: E501 "XLMRobertaModel": _HfExamplesInfo("intfloat/multilingual-e5-small"), # [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 # The model on Huggingface is currently being updated, # hence I temporarily mark it as not available online "PrithviGeoSpatialMAE": _HfExamplesInfo("ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11", # noqa: E501 is_available_online=False), } _CROSS_ENCODER_EXAMPLE_MODELS = { # [Text-only] "BertForSequenceClassification": _HfExamplesInfo("cross-encoder/ms-marco-MiniLM-L-6-v2"), # noqa: E501 "RobertaForSequenceClassification": _HfExamplesInfo("cross-encoder/quora-roberta-base"), # noqa: E501 "XLMRobertaForSequenceClassification": _HfExamplesInfo("BAAI/bge-reranker-v2-m3"), # noqa: E501 } _MULTIMODAL_EXAMPLE_MODELS = { # [Decoder-only] "AriaForConditionalGeneration": _HfExamplesInfo("rhymes-ai/Aria"), "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 "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 "FuyuForCausalLM": _HfExamplesInfo("adept/fuyu-8b"), "Gemma3ForConditionalGeneration": _HfExamplesInfo("google/gemma-3-4b-it", min_transformers_version="4.50"), "GLM4VForCausalLM": _HfExamplesInfo("THUDM/glm-4v-9b", trust_remote_code=True, hf_overrides={"architectures": ["GLM4VForCausalLM"]}), # noqa: E501 "H2OVLChatModel": _HfExamplesInfo("h2oai/h2ovl-mississippi-800m", extras={"2b": "h2oai/h2ovl-mississippi-2b"}), # noqa: E501 "InternVLChatModel": _HfExamplesInfo("OpenGVLab/InternVL2-1B", extras={"2B": "OpenGVLab/InternVL2-2B"}, # noqa: E501 trust_remote_code=True), "Idefics3ForConditionalGeneration": _HfExamplesInfo("HuggingFaceM4/Idefics3-8B-Llama3", # noqa: E501 {"tiny": "HuggingFaceTB/SmolVLM-256M-Instruct"}), # 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", max_transformers_version="4.48", transformers_version_reason="Use of deprecated imports which have been removed.", # noqa: E501 trust_remote_code=True), "MiniCPMV": _HfExamplesInfo("openbmb/MiniCPM-Llama3-V-2_5", extras={"2.6": "openbmb/MiniCPM-V-2_6"}, # noqa: E501 trust_remote_code=True), "MolmoForCausalLM": _HfExamplesInfo("allenai/Molmo-7B-D-0924", max_transformers_version="4.48", transformers_version_reason="Use of private method which no longer exists.", # 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), "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, extras={"phi3.5": "microsoft/Phi-3.5-vision-instruct"}), # noqa: E501 "Phi4MMForCausalLM": _HfExamplesInfo("microsoft/Phi-4-multimodal-instruct", trust_remote_code=True), "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 min_transformers_version="4.49"), # noqa: E501 "SkyworkR1VChatModel": _HfExamplesInfo("Skywork/Skywork-R1V-38B"), "UltravoxModel": _HfExamplesInfo("fixie-ai/ultravox-v0_5-llama-3_2-1b", # noqa: E501 trust_remote_code=True), # [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="facebook/bart-base", 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 } _SPECULATIVE_DECODING_EXAMPLE_MODELS = { "EAGLEModel": _HfExamplesInfo("JackFram/llama-68m", speculative_model="abhigoyal/vllm-eagle-llama-68m-random"), # noqa: E501 "MedusaModel": _HfExamplesInfo("JackFram/llama-68m", speculative_model="abhigoyal/vllm-medusa-llama-68m-random"), # noqa: E501 "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), } _TRANSFORMERS_MODELS = { "TransformersForCausalLM": _HfExamplesInfo("ArthurZ/Ilama-3.2-1B", trust_remote_code=True), # noqa: E501 } _EXAMPLE_MODELS = { **_TEXT_GENERATION_EXAMPLE_MODELS, **_EMBEDDING_EXAMPLE_MODELS, **_CROSS_ENCODER_EXAMPLE_MODELS, **_MULTIMODAL_EXAMPLE_MODELS, **_SPECULATIVE_DECODING_EXAMPLE_MODELS, **_TRANSFORMERS_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)