vllm/tests/models/registry.py
intervitens 5b1aca2ae3
[Bugfix] Fix GLM4 model (#16618)
Signed-off-by: intervitens <intervitens@tutanota.com>
2025-04-17 03:35:07 -07:00

431 lines
25 KiB
Python

# 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),
"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),
"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"),
"Glm4ForCausalLM": _HfExamplesInfo(
"THUDM/GLM-4-32B-0414",
is_available_online=False,
min_transformers_version="4.52.dev0"
),
"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),
"MiniMaxText01ForCausalLM": _HfExamplesInfo("MiniMaxAI/MiniMax-Text-01",
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),
"Plamo2ForCausalLM": _HfExamplesInfo("pfnet/plamo-2-1b",
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"),
"Qwen3ForCausalLM": _HfExamplesInfo(
"Qwen/Qwen3-8B",
is_available_online=False,
min_transformers_version="4.51"
),
"Qwen3MoeForCausalLM": _HfExamplesInfo(
"Qwen/Qwen3-MoE-15B-A2B",
is_available_online=False,
min_transformers_version="4.51"
),
"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
"ModernBertForSequenceClassification":
_HfExamplesInfo("Alibaba-NLP/gte-reranker-modernbert-base",
min_transformers_version="4.49"),
}
_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
"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
max_transformers_version="4.48", # noqa: E501
transformers_version_reason="HF model is not compatible."), # 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
"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
min_transformers_version="4.51"),
"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),
"Mistral3ForConditionalGeneration": _HfExamplesInfo("mistralai/Mistral-Small-3.1-24B-Instruct-2503", # noqa: E501
min_transformers_version="4.50", # 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),
"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),
"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"),
"SmolVLMForConditionalGeneration": _HfExamplesInfo("HuggingFaceTB/SmolVLM2-2.2B-Instruct"), # noqa: E501
"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="Isotr0py/Florence-2-tokenizer",
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),
"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
}
_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)