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Commit 90e10dee authored by zhuwenwen's avatar zhuwenwen
Browse files

[tests] update models

parent d7d4623e
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tests/models/registry.py
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......@@ -4,11 +4,13 @@ from collections.abc import Mapping, Set
from dataclasses import dataclass, field
from typing import Any, Literal, Optional
import os
import pytest
from packaging.version import Version
from transformers import __version__ as TRANSFORMERS_VERSION
@dataclass(frozen=True)
class _HfExamplesInfo:
default: str
......@@ -107,302 +109,304 @@ class _HfExamplesInfo:
pytest.skip(msg)
models_path_prefix = os.getenv('VLLM_OPTEST_MODELS_PATH') or os.getenv("OPTEST_MODELS_PATH")
# yapf: disable
_TEXT_GENERATION_EXAMPLE_MODELS = {
# [Decoder-only]
"AquilaModel": _HfExamplesInfo("BAAI/AquilaChat-7B",
"AquilaModel": _HfExamplesInfo(os.path.join(models_path_prefix, "BAAI/AquilaChat-7B"),
trust_remote_code=True),
"AquilaForCausalLM": _HfExamplesInfo("BAAI/AquilaChat2-7B",
"AquilaForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "BAAI/AquilaChat2-7B"),
trust_remote_code=True),
"ArcticForCausalLM": _HfExamplesInfo("Snowflake/snowflake-arctic-instruct",
"ArcticForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "Snowflake/snowflake-arctic-instruct"),
trust_remote_code=True),
"BaiChuanForCausalLM": _HfExamplesInfo("baichuan-inc/Baichuan-7B",
"BaiChuanForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "baichuan-inc/Baichuan-7B"),
trust_remote_code=True),
"BaichuanForCausalLM": _HfExamplesInfo("baichuan-inc/Baichuan2-7B-chat",
"BaichuanForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "baichuan-inc/Baichuan2-7B-chat"),
trust_remote_code=True),
"BambaForCausalLM": _HfExamplesInfo("ibm-ai-platform/Bamba-9B"),
"BloomForCausalLM": _HfExamplesInfo("bigscience/bloom-560m",
"BambaForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "ibm-ai-platform/Bamba-9B")),
"BloomForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "bigscience/bloom-560m"),
{"1b": "bigscience/bloomz-1b1"}),
"ChatGLMModel": _HfExamplesInfo("THUDM/chatglm3-6b",
"ChatGLMModel": _HfExamplesInfo(os.path.join(models_path_prefix, "THUDM/chatglm3-6b"),
trust_remote_code=True,
max_transformers_version="4.48"),
"ChatGLMForConditionalGeneration": _HfExamplesInfo("thu-coai/ShieldLM-6B-chatglm3", # noqa: E501
"ChatGLMForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "thu-coai/ShieldLM-6B-chatglm3"), # noqa: E501
trust_remote_code=True),
"CohereForCausalLM": _HfExamplesInfo("CohereForAI/c4ai-command-r-v01",
"CohereForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "CohereForAI/c4ai-command-r-v01"),
trust_remote_code=True),
"Cohere2ForCausalLM": _HfExamplesInfo("CohereForAI/c4ai-command-r7b-12-2024", # noqa: E501
"Cohere2ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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
"DbrxForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "databricks/dbrx-instruct")),
"DeciLMForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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
"DeepseekForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "deepseek-ai/deepseek-llm-7b-chat")),
"DeepseekV2ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "deepseek-ai/DeepSeek-V2-Lite-Chat"), # noqa: E501
trust_remote_code=True),
"DeepseekV3ForCausalLM": _HfExamplesInfo("deepseek-ai/DeepSeek-V3", # noqa: E501
"DeepseekV3ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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-1.1-2b-it"),
"Gemma2ForCausalLM": _HfExamplesInfo("google/gemma-2-9b"),
"Gemma3ForCausalLM": _HfExamplesInfo("google/gemma-3-1b-it"),
"GlmForCausalLM": _HfExamplesInfo("THUDM/glm-4-9b-chat-hf"),
"ExaoneForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "LGAI-EXAONE/EXAONE-3.0-7.8B-Instruct")), # noqa: E501
"Fairseq2LlamaForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "mgleize/fairseq2-dummy-Llama-3.2-1B")), # noqa: E501
"FalconForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "tiiuae/falcon-7b")),
"GemmaForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "google/gemma-1.1-2b-it")),
"Gemma2ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "google/gemma-2-9b")),
"Gemma3ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "google/gemma-3-1b-it")),
"GlmForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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("openai-community/gpt2",
"GPT2LMHeadModel": _HfExamplesInfo(os.path.join(models_path_prefix, "openai-community/gpt2"),
{"alias": "gpt2"}),
"GPTBigCodeForCausalLM": _HfExamplesInfo("bigcode/starcoder",
{"tiny": "bigcode/tiny_starcoder_py"}), # noqa: E501
"GPTJForCausalLM": _HfExamplesInfo("Milos/slovak-gpt-j-405M",
{"6b": "EleutherAI/gpt-j-6b"}),
"GPTNeoXForCausalLM": _HfExamplesInfo("EleutherAI/pythia-70m",
{"1b": "EleutherAI/pythia-1.4b"}),
"GraniteForCausalLM": _HfExamplesInfo("ibm/PowerLM-3b"),
"GraniteMoeForCausalLM": _HfExamplesInfo("ibm/PowerMoE-3b"),
"GraniteMoeSharedForCausalLM": _HfExamplesInfo("ibm-research/moe-7b-1b-active-shared-experts"), # 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",
"GPTBigCodeForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "bigcode/starcoder"),
{"tiny": os.path.join(models_path_prefix, "bigcode/tiny_starcoder_py")}), # noqa: E501
"GPTJForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "Milos/slovak-gpt-j-405M"),
{"6b": os.path.join(models_path_prefix, "EleutherAI/gpt-j-6b")}),
"GPTNeoXForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "EleutherAI/pythia-70m"),
{"1b": os.path.join(models_path_prefix, "EleutherAI/pythia-1.4b")}),
"GraniteForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "ibm/PowerLM-3b")),
"GraniteMoeForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "ibm/PowerMoE-3b")),
"GraniteMoeSharedForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "ibm-research/moe-7b-1b-active-shared-experts")), # noqa: E501
"Grok1ModelForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "hpcai-tech/grok-1"),
trust_remote_code=True),
"InternLMForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "internlm/internlm-chat-7b"),
trust_remote_code=True),
"InternLM2ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "internlm/internlm2-chat-7b"),
trust_remote_code=True),
"InternLM2VEForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "OpenGVLab/Mono-InternVL-2B"),
trust_remote_code=True),
"InternLM3ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "internlm/internlm3-8b-instruct"),
trust_remote_code=True),
"JAISLMHeadModel": _HfExamplesInfo(os.path.join(models_path_prefix, "inceptionai/jais-13b-chat")),
"JambaForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "ai21labs/AI21-Jamba-1.5-Mini"),
extras={"tiny": os.path.join(models_path_prefix, "ai21labs/Jamba-tiny-dev")}), # noqa: E501
"LlamaForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "meta-llama/Llama-3.2-1B-Instruct")),
"LLaMAForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "decapoda-research/llama-7b-hf"),
is_available_online=False),
"MambaForCausalLM": _HfExamplesInfo("state-spaces/mamba-130m-hf"),
"Mamba2ForCausalLM": _HfExamplesInfo("mistralai/Mamba-Codestral-7B-v0.1",
"MambaForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "state-spaces/mamba-130m-hf")),
"Mamba2ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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",
"FalconMambaForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "tiiuae/falcon-mamba-7b-instruct")), # noqa: E501
"MiniCPMForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "openbmb/MiniCPM-2B-sft-bf16"),
trust_remote_code=True),
"MiniCPM3ForCausalLM": _HfExamplesInfo("openbmb/MiniCPM3-4B",
"MiniCPM3ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "openbmb/MiniCPM3-4B"),
trust_remote_code=True),
"MiniMaxText01ForCausalLM": _HfExamplesInfo("MiniMaxAI/MiniMax-Text-01",
"MiniMaxText01ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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
{"falcon3": "ehristoforu/Falcon3-MoE-2x7B-Insruct"}), # 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-125m",
{"1b": "facebook/opt-iml-max-1.3b"}),
"OrionForCausalLM": _HfExamplesInfo("OrionStarAI/Orion-14B-Chat",
"MistralForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "mistralai/Mistral-7B-Instruct-v0.1")),
"MixtralForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "mistralai/Mixtral-8x7B-Instruct-v0.1"), # noqa: E501
{"falcon3": os.path.join(models_path_prefix, "ehristoforu/Falcon3-MoE-2x7B-Insruct")}), # noqa: E501
"QuantMixtralForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "mistral-community/Mixtral-8x22B-v0.1-AWQ")), # noqa: E501
"MptForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "mpt"), is_available_online=False),
"MPTForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "mosaicml/mpt-7b")),
"NemotronForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "nvidia/Minitron-8B-Base")),
"OlmoForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "allenai/OLMo-1B-hf")),
"Olmo2ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "shanearora/OLMo-7B-1124-hf")),
"OlmoeForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "allenai/OLMoE-1B-7B-0924-Instruct")),
"OPTForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "facebook/opt-125m"),
{"1b": os.path.join(models_path_prefix, "facebook/opt-iml-max-1.3b")}),
"OrionForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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",
"PersimmonForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "adept/persimmon-8b-chat")),
"PhiForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "microsoft/phi-2")),
"Phi3ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "microsoft/Phi-3-mini-4k-instruct")),
"Phi3SmallForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "microsoft/Phi-3-small-8k-instruct"),
trust_remote_code=True),
"PhiMoEForCausalLM": _HfExamplesInfo("microsoft/Phi-3.5-MoE-instruct",
"PhiMoEForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "microsoft/Phi-3.5-MoE-instruct"),
trust_remote_code=True),
"Plamo2ForCausalLM": _HfExamplesInfo("pfnet/plamo-2-1b",
"Plamo2ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "pfnet/plamo-2-1b"),
trust_remote_code=True),
"QWenLMHeadModel": _HfExamplesInfo("Qwen/Qwen-7B-Chat",
"QWenLMHeadModel": _HfExamplesInfo(os.path.join(models_path_prefix, "Qwen/Qwen-7B-Chat"),
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"),
"Qwen2ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "Qwen/Qwen2-0.5B-Instruct"),
extras={"2.5": os.path.join(models_path_prefix, "Qwen/Qwen2.5-0.5B-Instruct")}), # noqa: E501
"Qwen2MoeForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "Qwen/Qwen1.5-MoE-A2.7B-Chat")),
"Qwen3ForCausalLM": _HfExamplesInfo(
"Qwen/Qwen3-8B",
os.path.join(models_path_prefix, "Qwen/Qwen3-8B"),
is_available_online=False,
min_transformers_version="4.51"
),
"Qwen3MoeForCausalLM": _HfExamplesInfo(
"Qwen/Qwen3-MoE-15B-A2B",
os.path.join(models_path_prefix, "Qwen/Qwen3-MoE-15B-A2B"),
is_available_online=False,
min_transformers_version="4.51"
),
"RWForCausalLM": _HfExamplesInfo("tiiuae/falcon-40b",
"RWForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "tiiuae/falcon-40b"),
is_available_online=False),
"StableLMEpochForCausalLM": _HfExamplesInfo("stabilityai/stablelm-zephyr-3b", # noqa: E501
"StableLMEpochForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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",
"StableLmForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "stabilityai/stablelm-3b-4e1t")),
"Starcoder2ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "bigcode/starcoder2-3b")),
"SolarForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "upstage/solar-pro-preview-instruct")),
"TeleChat2ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "Tele-AI/TeleChat2-3B"),
trust_remote_code=True),
"TeleFLMForCausalLM": _HfExamplesInfo("CofeAI/FLM-2-52B-Instruct-2407",
"TeleFLMForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "CofeAI/FLM-2-52B-Instruct-2407"),
trust_remote_code=True),
"XverseForCausalLM": _HfExamplesInfo("xverse/XVERSE-7B-Chat",
"XverseForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "xverse/XVERSE-7B-Chat"),
is_available_online=False,
trust_remote_code=True),
"Zamba2ForCausalLM": _HfExamplesInfo("Zyphra/Zamba2-7B-instruct"),
"Zamba2ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "Zyphra/Zamba2-7B-instruct")),
# [Encoder-decoder]
"BartModel": _HfExamplesInfo("facebook/bart-base"),
"BartForConditionalGeneration": _HfExamplesInfo("facebook/bart-large-cnn"),
"BartModel": _HfExamplesInfo(os.path.join(models_path_prefix, "facebook/bart-base")),
"BartForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "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"),
"GteModel": _HfExamplesInfo("Snowflake/snowflake-arctic-embed-m-v2.0",
trust_remote_code=True),
"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"),
"NomicBertModel": _HfExamplesInfo("Snowflake/snowflake-arctic-embed-m-long", # noqa: E501
trust_remote_code=True),
"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"),
"BertModel": _HfExamplesInfo(os.path.join(models_path_prefix, "BAAI/bge-base-en-v1.5")),
"Gemma2Model": _HfExamplesInfo(os.path.join(models_path_prefix, "BAAI/bge-multilingual-gemma2")),
"GritLM": _HfExamplesInfo(os.path.join(models_path_prefix, "parasail-ai/GritLM-7B-vllm")),
"GteModel": _HfExamplesInfo(os.path.join(models_path_prefix, "Snowflake/snowflake-arctic-embed-m-v2.0"),
trust_remote_code=True),
"InternLM2ForRewardModel": _HfExamplesInfo(os.path.join(models_path_prefix, "internlm/internlm2-1_8b-reward"),
trust_remote_code=True),
"JambaForSequenceClassification": _HfExamplesInfo(os.path.join(models_path_prefix, "ai21labs/Jamba-tiny-reward-dev")), # noqa: E501
"LlamaModel": _HfExamplesInfo(os.path.join(models_path_prefix, "llama"), is_available_online=False),
"MistralModel": _HfExamplesInfo(os.path.join(models_path_prefix, "intfloat/e5-mistral-7b-instruct")),
"NomicBertModel": _HfExamplesInfo(os.path.join(models_path_prefix, "Snowflake/snowflake-arctic-embed-m-long"), # noqa: E501
trust_remote_code=True),
"Qwen2Model": _HfExamplesInfo(os.path.join(models_path_prefix, "ssmits/Qwen2-7B-Instruct-embed-base")),
"Qwen2ForRewardModel": _HfExamplesInfo(os.path.join(models_path_prefix, "Qwen/Qwen2.5-Math-RM-72B")),
"Qwen2ForProcessRewardModel": _HfExamplesInfo(os.path.join(models_path_prefix, "Qwen/Qwen2.5-Math-PRM-7B")),
"Qwen2ForSequenceClassification": _HfExamplesInfo(os.path.join(models_path_prefix, "jason9693/Qwen2.5-1.5B-apeach")), # noqa: E501
"RobertaModel": _HfExamplesInfo(os.path.join(models_path_prefix, "sentence-transformers/stsb-roberta-base-v2")), # noqa: E501
"RobertaForMaskedLM": _HfExamplesInfo(os.path.join(models_path_prefix, "sentence-transformers/all-roberta-large-v1")), # noqa: E501
"XLMRobertaModel": _HfExamplesInfo(os.path.join(models_path_prefix, "intfloat/multilingual-e5-small")),
# [Multimodal]
"LlavaNextForConditionalGeneration": _HfExamplesInfo("royokong/e5-v"),
"Phi3VForCausalLM": _HfExamplesInfo("TIGER-Lab/VLM2Vec-Full",
"LlavaNextForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "royokong/e5-v")),
"Phi3VForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "TIGER-Lab/VLM2Vec-Full"),
trust_remote_code=True),
"Qwen2VLForConditionalGeneration": _HfExamplesInfo("MrLight/dse-qwen2-2b-mrl-v1"), # noqa: E501
"Qwen2VLForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "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
"PrithviGeoSpatialMAE": _HfExamplesInfo(os.path.join(models_path_prefix, "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"), # noqa: E501
"BertForSequenceClassification": _HfExamplesInfo(os.path.join(models_path_prefix, "cross-encoder/ms-marco-MiniLM-L-6-v2")), # noqa: E501
"RobertaForSequenceClassification": _HfExamplesInfo(os.path.join(models_path_prefix, "cross-encoder/quora-roberta-base")), # noqa: E501
"XLMRobertaForSequenceClassification": _HfExamplesInfo(os.path.join(models_path_prefix, "BAAI/bge-reranker-v2-m3")), # noqa: E501
"ModernBertForSequenceClassification": _HfExamplesInfo(os.path.join(models_path_prefix, "Alibaba-NLP/gte-reranker-modernbert-base")), # 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
"DeepseekVLV2ForCausalLM": _HfExamplesInfo("deepseek-ai/deepseek-vl2-tiny", # noqa: E501
extras={"fork": "Isotr0py/deepseek-vl2-tiny"}, # noqa: E501
"AriaForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "rhymes-ai/Aria")),
"AyaVisionForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "CohereForAI/aya-vision-8b")), # noqa: E501
"Blip2ForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "Salesforce/blip2-opt-2.7b"), # noqa: E501
extras={"6b": os.path.join(models_path_prefix, "Salesforce/blip2-opt-6.7b")}), # noqa: E501
"ChameleonForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "facebook/chameleon-7b")), # noqa: E501
"DeepseekVLV2ForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "deepseek-ai/deepseek-vl2-tiny"), # noqa: E501
extras={"fork": os.path.join(models_path_prefix, "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"),
"GraniteSpeechForConditionalGeneration": _HfExamplesInfo("ibm-granite/granite-speech-3.3-8b", # noqa: E501
"FuyuForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "adept/fuyu-8b")),
"Gemma3ForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "google/gemma-3-4b-it")),
"GraniteSpeechForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "ibm-granite/granite-speech-3.3-8b"), # noqa: E501
min_transformers_version="4.52.0"), # noqa: E501
"GLM4VForCausalLM": _HfExamplesInfo("THUDM/glm-4v-9b",
"GLM4VForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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
"H2OVLChatModel": _HfExamplesInfo(os.path.join(models_path_prefix, "h2oai/h2ovl-mississippi-800m"),
extras={"2b": os.path.join(models_path_prefix, "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
"InternVLChatModel": _HfExamplesInfo(os.path.join(models_path_prefix, "OpenGVLab/InternVL2-1B"),
extras={"2B": os.path.join(models_path_prefix, "OpenGVLab/InternVL2-1B")}, # 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
"Idefics3ForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "HuggingFaceM4/Idefics3-8B-Llama3"), # noqa: E501
{"tiny": os.path.join(models_path_prefix, "HuggingFaceTB/SmolVLM-256M-Instruct")}), # noqa: E501
"KimiVLForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "moonshotai/Kimi-VL-A3B-Instruct"), # noqa: E501
extras={"thinking": os.path.join(models_path_prefix, "moonshotai/Kimi-VL-A3B-Thinking")}, # noqa: E501
trust_remote_code=True),
"Llama4ForConditionalGeneration": _HfExamplesInfo("meta-llama/Llama-4-Scout-17B-16E-Instruct", # noqa: E501
"Llama4ForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "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
"LlavaForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "llava-hf/llava-1.5-7b-hf"),
extras={"mistral": os.path.join(models_path_prefix, "mistral-community/pixtral-12b"), # noqa: E501
"mistral-fp8": os.path.join(models_path_prefix, "nm-testing/pixtral-12b-FP8-dynamic")}), # noqa: E501
"LlavaNextForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "llava-hf/llava-v1.6-mistral-7b-hf")), # noqa: E501
"LlavaNextVideoForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "llava-hf/LLaVA-NeXT-Video-7B-hf")), # noqa: E501
"LlavaOnevisionForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "llava-hf/llava-onevision-qwen2-0.5b-ov-hf")), # noqa: E501
"MantisForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "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",
"MiniCPMO": _HfExamplesInfo(os.path.join(models_path_prefix, "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
"MiniCPMV": _HfExamplesInfo(os.path.join(models_path_prefix, "openbmb/MiniCPM-Llama3-V-2_5"),
extras={"2.6": os.path.join(models_path_prefix, "openbmb/MiniCPM-V-2_6")}, # noqa: E501
trust_remote_code=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",
"Mistral3ForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "mistralai/Mistral-Small-3.1-24B-Instruct-2503"), # noqa: E501
extras={"fp8": os.path.join(models_path_prefix, "nm-testing/Mistral-Small-3.1-24B-Instruct-2503-FP8-dynamic")}), # noqa: E501
"MolmoForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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
extras={"olmo": os.path.join(models_path_prefix, "allenai/Molmo-7B-O-0924")}, # noqa: E501
trust_remote_code=True),
"NVLM_D": _HfExamplesInfo("nvidia/NVLM-D-72B",
"NVLM_D": _HfExamplesInfo(os.path.join(models_path_prefix, "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",
"PaliGemmaForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "google/paligemma-3b-mix-224"), # noqa: E501
extras={"v2": os.path.join(models_path_prefix, "google/paligemma2-3b-ft-docci-448")}), # noqa: E501
"Phi3VForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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",
extras={"phi3.5": os.path.join(models_path_prefix, "microsoft/Phi-3.5-vision-instruct"),}), # noqa: E501
"Phi4MMForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "microsoft/Phi-4-multimodal-instruct"),
trust_remote_code=True),
"PixtralForConditionalGeneration": _HfExamplesInfo("mistralai/Pixtral-12B-2409", # noqa: E501
"PixtralForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "mistralai/Pixtral-12B-2409"), # noqa: E501
tokenizer_mode="mistral"),
"QwenVLForConditionalGeneration": _HfExamplesInfo("Qwen/Qwen-VL",
extras={"chat": "Qwen/Qwen-VL-Chat"}, # noqa: E501
"QwenVLForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "Qwen/Qwen-VL"),
extras={"chat": os.path.join(models_path_prefix, "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
"Qwen2_5OmniModel": _HfExamplesInfo("Qwen/Qwen2.5-Omni-7B", # noqa: E501
"Qwen2AudioForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "Qwen/Qwen2-Audio-7B-Instruct")), # noqa: E501
"Qwen2VLForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "Qwen/Qwen2-VL-2B-Instruct")), # noqa: E501
"Qwen2_5_VLForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "Qwen/Qwen2.5-VL-3B-Instruct")), # noqa: E501
"Qwen2_5OmniModel": _HfExamplesInfo(os.path.join(models_path_prefix, "Qwen/Qwen2.5-Omni-7B"), # noqa: E501
min_transformers_version="4.52"), # 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
"SkyworkR1VChatModel": _HfExamplesInfo(os.path.join(models_path_prefix, "Skywork/Skywork-R1V-38B")),
"SmolVLMForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "HuggingFaceTB/SmolVLM2-2.2B-Instruct")), # noqa: E501
"UltravoxModel": _HfExamplesInfo(os.path.join(models_path_prefix, "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",
"Florence2ForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "microsoft/Florence-2-base"), # noqa: E501
tokenizer=os.path.join(models_path_prefix, "Isotr0py/Florence-2-tokenizer"),
trust_remote_code=True), # noqa: E501
"MllamaForConditionalGeneration": _HfExamplesInfo("meta-llama/Llama-3.2-11B-Vision-Instruct"), # noqa: E501
"Llama4ForConditionalGeneration": _HfExamplesInfo("meta-llama/Llama-4-Scout-17B-16E-Instruct"), # noqa: E501
"WhisperForConditionalGeneration": _HfExamplesInfo("openai/whisper-large-v3"), # noqa: E501
"MllamaForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "meta-llama/Llama-3.2-11B-Vision-Instruct")), # noqa: E501
"Llama4ForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "meta-llama/Llama-4-Scout-17B-16E-Instruct")), # noqa: E501
"WhisperForConditionalGeneration": _HfExamplesInfo(os.path.join(models_path_prefix, "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",
"EAGLEModel": _HfExamplesInfo(os.path.join(models_path_prefix, "JackFram/llama-68m"),
speculative_model=os.path.join(models_path_prefix, "abhigoyal/vllm-eagle-llama-68m-random")), # noqa: E501
"MedusaModel": _HfExamplesInfo(os.path.join(models_path_prefix, "JackFram/llama-68m"),
speculative_model=os.path.join(models_path_prefix, "abhigoyal/vllm-medusa-llama-68m-random")), # noqa: E501
"MLPSpeculatorPreTrainedModel": _HfExamplesInfo(os.path.join(models_path_prefix, "JackFram/llama-160m"),
speculative_model=os.path.join(models_path_prefix, "ibm-ai-platform/llama-160m-accelerator")), # noqa: E501
"DeepSeekMTPModel": _HfExamplesInfo(os.path.join(models_path_prefix, "luccafong/deepseek_mtp_main_random"),
speculative_model=os.path.join(models_path_prefix, "luccafong/deepseek_mtp_draft_random"), # noqa: E501
trust_remote_code=True),
"EagleLlamaForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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
speculative_model=os.path.join(models_path_prefix, "yuhuili/EAGLE-LLaMA3-Instruct-8B"),
tokenizer=os.path.join(models_path_prefix, "meta-llama/Meta-Llama-3-8B-Instruct")), # noqa: E501
"Eagle3LlamaForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "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"),
speculative_model=os.path.join(models_path_prefix, "yuhuili/EAGLE3-LLaMA3.1-Instruct-8B"),
tokenizer=os.path.join(models_path_prefix, "meta-llama/Llama-3.1-8B-Instruct")),
}
_TRANSFORMERS_MODELS = {
"TransformersForCausalLM": _HfExamplesInfo("ArthurZ/Ilama-3.2-1B", trust_remote_code=True), # noqa: E501
"TransformersForCausalLM": _HfExamplesInfo(os.path.join(models_path_prefix, "ArthurZ/Ilama-3.2-1B"), trust_remote_code=True), # noqa: E501
}
_EXAMPLE_MODELS = {
......
tests/models/test_gptq_bitblas.py
View file @ 90e10dee
......@@ -13,9 +13,11 @@ Run `pytest tests/models/test_bitblas.py`.
"""
from dataclasses import dataclass
import os
import pytest
from .utils import check_logprobs_close
from ..utils import models_path_prefix
@dataclass
......@@ -24,7 +26,7 @@ class ModelPair:
model_pairs = [
ModelPair(model_gptq="hxbgsyxh/opt-125m-4bit-128g"),
ModelPair(model_gptq=os.path.join(models_path_prefix, "hxbgsyxh/opt-125m-4bit-128g")),
]
......
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