[CI/Build] Remove unnecessary flags from test registry (#27353)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

docs/models/supported_models.md

@@ -374,8 +374,8 @@ th {
 | `GraniteMoeSharedForCausalLM` | Granite MoE Shared | `ibm-research/moe-7b-1b-active-shared-experts` (test model) | ✅︎ | ✅︎ |
 | `GritLM` | GritLM | `parasail-ai/GritLM-7B-vllm`. | ✅︎ | ✅︎ |
 | `Grok1ModelForCausalLM` | Grok1 | `hpcai-tech/grok-1`. | ✅︎ | ✅︎ |
-| `HunYuanDenseV1ForCausalLM` | Hunyuan-7B-Instruct-0124 | `tencent/Hunyuan-7B-Instruct-0124` | ✅︎ | ✅︎ |
-| `HunYuanMoEV1ForCausalLM` | Hunyuan-80B-A13B | `tencent/Hunyuan-A13B-Instruct`, `tencent/Hunyuan-A13B-Pretrain`, `tencent/Hunyuan-A13B-Instruct-FP8`, etc. | ✅︎ | ✅︎ |
+| `HunYuanDenseV1ForCausalLM` | Hunyuan Dense | `tencent/Hunyuan-7B-Instruct` | ✅︎ | ✅︎ |
+| `HunYuanMoEV1ForCausalLM` | Hunyuan-A13B | `tencent/Hunyuan-A13B-Instruct`, `tencent/Hunyuan-A13B-Pretrain`, `tencent/Hunyuan-A13B-Instruct-FP8`, etc. | ✅︎ | ✅︎ |
 | `HCXVisionForCausalLM` | HyperCLOVAX-SEED-Vision-Instruct-3B | `naver-hyperclovax/HyperCLOVAX-SEED-Vision-Instruct-3B` | | |
 | `InternLMForCausalLM` | InternLM | `internlm/internlm-7b`, `internlm/internlm-chat-7b`, etc. | ✅︎ | ✅︎ |
 | `InternLM2ForCausalLM` | InternLM2 | `internlm/internlm2-7b`, `internlm/internlm2-chat-7b`, etc. | ✅︎ | ✅︎ |

tests/distributed/test_pipeline_parallel.py

@@ -244,7 +244,7 @@ def _compare_tp(
     tokenizer_mode = model_info.tokenizer_mode
     hf_overrides = model_info.hf_overrides
     hf_config = get_config(model_id, trust_remote_code)
-    skip_tokenizer_init = model_info.skip_tokenizer_init
+    require_embed_inputs = model_info.require_embed_inputs
     max_num_seqs = model_info.max_num_seqs
 
     dtype = "float16"
@@ -299,8 +299,14 @@ def _compare_tp(
         common_args.extend(["--load-format", load_format])
     if hf_overrides:
         common_args.extend(["--hf-overrides", json.dumps(hf_overrides)])
-    if skip_tokenizer_init:
-        common_args.append("--skip-tokenizer-init")
+    if require_embed_inputs:
+        common_args.extend(
+            [
+                "--skip-tokenizer-init",
+                "--enable-prompt-embeds",
+                "--enable-mm-embeds",
+            ]
+        )
     if max_num_seqs:
         common_args.extend(["--max-num-seqs", f"{max_num_seqs}"])
 

tests/distributed/test_sequence_parallel.py

@@ -181,7 +181,7 @@ def _compare_sp(
     trust_remote_code = model_info.trust_remote_code
     tokenizer_mode = model_info.tokenizer_mode
     hf_overrides = model_info.hf_overrides
-    skip_tokenizer_init = model_info.skip_tokenizer_init
+    require_embed_inputs = model_info.require_embed_inputs
 
     if load_format == "dummy":
         # Avoid OOM
@@ -233,8 +233,14 @@ def _compare_sp(
         common_args.extend(["--load-format", load_format])
     if hf_overrides:
         common_args.extend(["--hf-overrides", json.dumps(hf_overrides)])
-    if skip_tokenizer_init:
-        common_args.append("--skip-tokenizer-init")
+    if require_embed_inputs:
+        common_args.extend(
+            [
+                "--skip-tokenizer-init",
+                "--enable-prompt-embeds",
+                "--enable-mm-embeds",
+            ]
+        )
 
     compilation_config = {
         "mode": CompilationMode.VLLM_COMPILE,

tests/entrypoints/openai/test_chat_template.py

@@ -114,7 +114,9 @@ def test_get_gen_prompt(
         trust_remote_code=model_info.trust_remote_code,
         revision=model_info.revision,
         hf_overrides=model_info.hf_overrides,
-        skip_tokenizer_init=model_info.skip_tokenizer_init,
+        skip_tokenizer_init=model_info.require_embed_inputs,
+        enable_prompt_embeds=model_info.require_embed_inputs,
+        enable_mm_embeds=model_info.require_embed_inputs,
         enforce_eager=model_info.enforce_eager,
         dtype=model_info.dtype,
     )

tests/entrypoints/test_chat_utils.py

@@ -1742,7 +1742,9 @@ def test_resolve_hf_chat_template(sample_json_schema, model, use_tools):
         revision=model_info.revision,
         trust_remote_code=model_info.trust_remote_code,
         hf_overrides=model_info.hf_overrides,
-        skip_tokenizer_init=model_info.skip_tokenizer_init,
+        skip_tokenizer_init=model_info.require_embed_inputs,
+        enable_prompt_embeds=model_info.require_embed_inputs,
+        enable_mm_embeds=model_info.require_embed_inputs,
         enforce_eager=model_info.enforce_eager,
         dtype=model_info.dtype,
     )
@@ -1842,7 +1844,9 @@ def test_resolve_hf_chat_template_kwargs(sample_json_schema, model, expected_kwa
         revision=model_info.revision,
         trust_remote_code=model_info.trust_remote_code,
         hf_overrides=model_info.hf_overrides,
-        skip_tokenizer_init=model_info.skip_tokenizer_init,
+        skip_tokenizer_init=model_info.require_embed_inputs,
+        enable_prompt_embeds=model_info.require_embed_inputs,
+        enable_mm_embeds=model_info.require_embed_inputs,
         enforce_eager=model_info.enforce_eager,
         dtype=model_info.dtype,
     )
@@ -1903,7 +1907,9 @@ def test_resolve_content_format_hf_defined(model, expected_format):
         revision=model_info.revision,
         trust_remote_code=model_info.trust_remote_code,
         hf_overrides=model_info.hf_overrides,
-        skip_tokenizer_init=model_info.skip_tokenizer_init,
+        skip_tokenizer_init=model_info.require_embed_inputs,
+        enable_prompt_embeds=model_info.require_embed_inputs,
+        enable_mm_embeds=model_info.require_embed_inputs,
         enforce_eager=model_info.enforce_eager,
         dtype=model_info.dtype,
     )
@@ -1961,7 +1967,9 @@ def test_resolve_content_format_fallbacks(model, expected_format):
         revision=model_info.revision,
         trust_remote_code=model_info.trust_remote_code,
         hf_overrides=model_info.hf_overrides,
-        skip_tokenizer_init=model_info.skip_tokenizer_init,
+        skip_tokenizer_init=model_info.require_embed_inputs,
+        enable_prompt_embeds=model_info.require_embed_inputs,
+        enable_mm_embeds=model_info.require_embed_inputs,
         enforce_eager=model_info.enforce_eager,
         dtype=model_info.dtype,
     )

tests/models/multimodal/generation/vlm_utils/core.py

@@ -71,8 +71,9 @@ def run_test(
         vllm_runner_kwargs_["tokenizer_mode"] = model_info.tokenizer_mode
     if model_info.hf_overrides:
         vllm_runner_kwargs_["hf_overrides"] = model_info.hf_overrides
-    if model_info.skip_tokenizer_init:
-        vllm_runner_kwargs_["skip_tokenizer_init"] = model_info.skip_tokenizer_init
+    if model_info.require_embed_inputs:
+        for k in ("skip_tokenizer_init", "enable_prompt_embeds", "enable_mm_embeds"):
+            vllm_runner_kwargs_[k] = model_info.require_embed_inputs
 
     if vllm_runner_kwargs:
         vllm_runner_kwargs_.update(vllm_runner_kwargs)

tests/models/multimodal/processing/test_common.py

@@ -108,7 +108,9 @@ def _test_processing_correctness(
         hf_overrides=model_info.hf_overrides,
         # Ensure that the cache can fit all of the data
         mm_processor_cache_gb=2048,
-        skip_tokenizer_init=model_info.skip_tokenizer_init,
+        skip_tokenizer_init=model_info.require_embed_inputs,
+        enable_prompt_embeds=model_info.require_embed_inputs,
+        enable_mm_embeds=model_info.require_embed_inputs,
         enforce_eager=model_info.enforce_eager,
         dtype=model_info.dtype,
     )

tests/models/multimodal/processing/test_tensor_schema.py

@@ -218,7 +218,9 @@ def test_model_tensor_schema(model_arch: str, model_id: str):
         revision=model_info.revision,
         trust_remote_code=model_info.trust_remote_code,
         hf_overrides=hf_overrides_fn,
-        skip_tokenizer_init=model_info.skip_tokenizer_init,
+        skip_tokenizer_init=model_info.require_embed_inputs,
+        enable_prompt_embeds=model_info.require_embed_inputs,
+        enable_mm_embeds=model_info.require_embed_inputs,
         enforce_eager=model_info.enforce_eager,
         dtype=model_info.dtype,
     )

tests/models/multimodal/test_mapping.py

@@ -59,7 +59,9 @@ def test_hf_model_weights_mapper(model_arch: str):
         revision=model_info.revision,
         trust_remote_code=model_info.trust_remote_code,
         hf_overrides=model_info.hf_overrides,
-        skip_tokenizer_init=model_info.skip_tokenizer_init,
+        skip_tokenizer_init=model_info.require_embed_inputs,
+        enable_prompt_embeds=model_info.require_embed_inputs,
+        enable_mm_embeds=model_info.require_embed_inputs,
         enforce_eager=model_info.enforce_eager,
         dtype=model_info.dtype,
     )

tests/models/registry.py

@@ -6,7 +6,6 @@ from dataclasses import dataclass, field
 from typing import Any, Literal
 
 import pytest
-import torch
 from packaging.version import Version
 from transformers import __version__ as TRANSFORMERS_VERSION
 
@@ -33,6 +32,11 @@ class _HfExamplesInfo:
     for speculative decoding.
     """
 
+    speculative_method: str | None = None
+    """
+    The method to use for speculative decoding.
+    """
+
     min_transformers_version: str | None = None
     """
     The minimum version of HF Transformers that is required to run this model.
@@ -48,9 +52,10 @@ class _HfExamplesInfo:
     The reason for the minimum/maximum version requirement.
     """
 
-    skip_tokenizer_init: bool = False
+    require_embed_inputs: bool = False
     """
-    If true, skip initialization of tokenizer and detokenizer. 
+    If `True`, enables prompt and multi-modal embedding inputs while
+    disabling tokenization.
     """
 
     dtype: ModelDType = "auto"
@@ -168,10 +173,7 @@ class _HfExamplesInfo:
 
 _TEXT_GENERATION_EXAMPLE_MODELS = {
     # [Decoder-only]
-    "ApertusForCausalLM": _HfExamplesInfo(
-        "swiss-ai/Apertus-8B-Instruct-2509",
-        min_transformers_version="4.56.0",
-    ),
+    "ApertusForCausalLM": _HfExamplesInfo("swiss-ai/Apertus-8B-Instruct-2509"),
     "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"),
@@ -192,7 +194,6 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
     ),
     "BambaForCausalLM": _HfExamplesInfo(
         "ibm-ai-platform/Bamba-9B-v1",
-        min_transformers_version="4.55.3",
         extras={"tiny": "hmellor/tiny-random-BambaForCausalLM"},
     ),
     "BloomForCausalLM": _HfExamplesInfo(
@@ -212,11 +213,7 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
         "CohereForAI/c4ai-command-r7b-12-2024",
         trust_remote_code=True,
     ),
-    "CwmForCausalLM": _HfExamplesInfo(
-        "facebook/cwm",
-        trust_remote_code=True,
-        is_available_online=False,
-    ),
+    "CwmForCausalLM": _HfExamplesInfo("facebook/cwm", min_transformers_version="4.58"),
     "DbrxForCausalLM": _HfExamplesInfo("databricks/dbrx-instruct"),
     "DeciLMForCausalLM": _HfExamplesInfo(
         "nvidia/Llama-3_3-Nemotron-Super-49B-v1",
@@ -232,18 +229,12 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
         trust_remote_code=True,
     ),
     "DeepseekV32ForCausalLM": _HfExamplesInfo("deepseek-ai/DeepSeek-V3.2-Exp"),
-    "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"
-    ),
+    "Ernie4_5ForCausalLM": _HfExamplesInfo("baidu/ERNIE-4.5-0.3B-PT"),
+    "Ernie4_5_MoeForCausalLM": _HfExamplesInfo("baidu/ERNIE-4.5-21B-A3B-PT"),
     "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"
-    ),
+    "Exaone4ForCausalLM": _HfExamplesInfo("LGAI-EXAONE/EXAONE-4.0-32B"),
     "Fairseq2LlamaForCausalLM": _HfExamplesInfo("mgleize/fairseq2-dummy-Llama-3.2-1B"),
     "FalconForCausalLM": _HfExamplesInfo("tiiuae/falcon-7b"),
     "FalconH1ForCausalLM": _HfExamplesInfo("tiiuae/Falcon-H1-0.5B-Base"),
@@ -251,14 +242,10 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
     "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"
-    ),
+    "Gemma3nForCausalLM": _HfExamplesInfo("google/gemma-3n-E2B-it"),
     "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"
-    ),
+    "Glm4MoeForCausalLM": _HfExamplesInfo("zai-org/GLM-4.5"),
     "GPT2LMHeadModel": _HfExamplesInfo("openai-community/gpt2", {"alias": "gpt2"}),
     "GPTBigCodeForCausalLM": _HfExamplesInfo(
         "bigcode/starcoder",
@@ -266,8 +253,6 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
             "tiny": "bigcode/tiny_starcoder_py",
             "santacoder": "bigcode/gpt_bigcode-santacoder",
         },
-        min_transformers_version="4.55.1",
-        transformers_version_reason="HF model broken in 4.55.0",
     ),
     "GPTJForCausalLM": _HfExamplesInfo(
         "Milos/slovak-gpt-j-405M", {"6b": "EleutherAI/gpt-j-6b"}
@@ -279,8 +264,7 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
     "GraniteForCausalLM": _HfExamplesInfo("ibm/PowerLM-3b"),
     "GraniteMoeForCausalLM": _HfExamplesInfo("ibm/PowerMoE-3b"),
     "GraniteMoeHybridForCausalLM": _HfExamplesInfo(
-        "ibm-granite/granite-4.0-tiny-preview",
-        min_transformers_version="4.55.3",
+        "ibm-granite/granite-4.0-tiny-preview"
     ),
     "GraniteMoeSharedForCausalLM": _HfExamplesInfo(
         "ibm-research/moe-7b-1b-active-shared-experts"
@@ -288,15 +272,10 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
     "Grok1ModelForCausalLM": _HfExamplesInfo(
         "hpcai-tech/grok-1", trust_remote_code=True
     ),
+    "HunYuanDenseV1ForCausalLM": _HfExamplesInfo("tencent/Hunyuan-7B-Instruct"),
     "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,
-    ),
     "InternLMForCausalLM": _HfExamplesInfo(
         "internlm/internlm-chat-7b", trust_remote_code=True
     ),
@@ -312,15 +291,12 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
     "JAISLMHeadModel": _HfExamplesInfo("inceptionai/jais-13b-chat"),
     "JambaForCausalLM": _HfExamplesInfo(
         "ai21labs/AI21-Jamba-1.5-Mini",
-        min_transformers_version="4.55.3",
         extras={
             "tiny": "ai21labs/Jamba-tiny-dev",
             "random": "ai21labs/Jamba-tiny-random",
         },
     ),
-    "Lfm2ForCausalLM": _HfExamplesInfo(
-        "LiquidAI/LFM2-1.2B", min_transformers_version="4.54"
-    ),
+    "Lfm2ForCausalLM": _HfExamplesInfo("LiquidAI/LFM2-1.2B"),
     "Lfm2MoeForCausalLM": _HfExamplesInfo(
         "LiquidAI/LFM2-8B-A1B", min_transformers_version="4.58"
     ),
@@ -338,7 +314,6 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
     ),
     "Llama4ForCausalLM": _HfExamplesInfo(
         "meta-llama/Llama-4-Scout-17B-16E-Instruct",
-        is_available_online=False,
     ),
     "LongcatFlashForCausalLM": _HfExamplesInfo(
         "meituan-longcat/LongCat-Flash-Chat", trust_remote_code=True
@@ -346,7 +321,6 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
     "MambaForCausalLM": _HfExamplesInfo("state-spaces/mamba-130m-hf"),
     "Mamba2ForCausalLM": _HfExamplesInfo(
         "mistralai/Mamba-Codestral-7B-v0.1",
-        min_transformers_version="4.55.3",
         extras={
             "random": "yujiepan/mamba2-codestral-v0.1-tiny-random",
         },
@@ -421,7 +395,6 @@ _TEXT_GENERATION_EXAMPLE_MODELS = {
     "SeedOssForCausalLM": _HfExamplesInfo(
         "ByteDance-Seed/Seed-OSS-36B-Instruct",
         trust_remote_code=True,
-        is_available_online=False,
     ),
     "SmolLM3ForCausalLM": _HfExamplesInfo("HuggingFaceTB/SmolLM3-3B"),
     "StableLMEpochForCausalLM": _HfExamplesInfo("stabilityai/stablelm-zephyr-3b"),
@@ -488,7 +461,8 @@ _EMBEDDING_EXAMPLE_MODELS = {
     "RobertaForMaskedLM": _HfExamplesInfo("sentence-transformers/all-roberta-large-v1"),
     "XLMRobertaModel": _HfExamplesInfo("intfloat/multilingual-e5-small"),
     "BertSpladeSparseEmbeddingModel": _HfExamplesInfo(
-        "naver/splade-v3", is_available_online=False
+        "naver/splade-v3",
+        hf_overrides={"architectures": ["BertSpladeSparseEmbeddingModel"]},
     ),
     # [Multimodal]
     "CLIPModel": _HfExamplesInfo("openai/clip-vit-base-patch32"),
@@ -499,18 +473,17 @@ _EMBEDDING_EXAMPLE_MODELS = {
     "Qwen2VLForConditionalGeneration": _HfExamplesInfo("MrLight/dse-qwen2-2b-mrl-v1"),
     "PrithviGeoSpatialMAE": _HfExamplesInfo(
         "ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11",
-        dtype=torch.float16,
+        dtype="float16",
         enforce_eager=True,
-        skip_tokenizer_init=True,
-        # This is to avoid the model
-        # going OOM in CI
+        require_embed_inputs=True,
+        # This is to avoid the model going OOM in CI
         max_num_seqs=32,
     ),
     "Terratorch": _HfExamplesInfo(
         "ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11",
-        dtype=torch.float16,
+        dtype="float16",
         enforce_eager=True,
-        skip_tokenizer_init=True,
+        require_embed_inputs=True,
         # This is to avoid the model going OOM in CI
         max_num_seqs=32,
     ),
@@ -598,10 +571,7 @@ _MULTIMODAL_EXAMPLE_MODELS = {
     ),
     "FuyuForCausalLM": _HfExamplesInfo("adept/fuyu-8b"),
     "Gemma3ForConditionalGeneration": _HfExamplesInfo("google/gemma-3-4b-it"),
-    "Gemma3nForConditionalGeneration": _HfExamplesInfo(
-        "google/gemma-3n-E2B-it",
-        min_transformers_version="4.53",
-    ),
+    "Gemma3nForConditionalGeneration": _HfExamplesInfo("google/gemma-3n-E2B-it"),
     "GraniteSpeechForConditionalGeneration": _HfExamplesInfo(
         "ibm-granite/granite-speech-3.3-2b"
     ),
@@ -611,9 +581,7 @@ _MULTIMODAL_EXAMPLE_MODELS = {
         hf_overrides={"architectures": ["GLM4VForCausalLM"]},
     ),
     "Glm4vForConditionalGeneration": _HfExamplesInfo("zai-org/GLM-4.1V-9B-Thinking"),
-    "Glm4vMoeForConditionalGeneration": _HfExamplesInfo(
-        "zai-org/GLM-4.5V", min_transformers_version="4.56"
-    ),
+    "Glm4vMoeForConditionalGeneration": _HfExamplesInfo("zai-org/GLM-4.5V"),
     "H2OVLChatModel": _HfExamplesInfo(
         "h2oai/h2ovl-mississippi-800m",
         trust_remote_code=True,
@@ -627,9 +595,7 @@ _MULTIMODAL_EXAMPLE_MODELS = {
     ),
     "Idefics3ForConditionalGeneration": _HfExamplesInfo(
         "HuggingFaceM4/Idefics3-8B-Llama3",
-        {"tiny": "HuggingFaceTB/SmolVLM-256M-Instruct"},
-        min_transformers_version="4.56",
-        transformers_version_reason="HF model broken in 4.55",
+        extras={"tiny": "HuggingFaceTB/SmolVLM-256M-Instruct"},
     ),
     "InternS1ForConditionalGeneration": _HfExamplesInfo(
         "internlm/Intern-S1", trust_remote_code=True
@@ -781,13 +747,11 @@ _MULTIMODAL_EXAMPLE_MODELS = {
         "Qwen/Qwen3-VL-4B-Instruct",
         max_model_len=4096,
         min_transformers_version="4.57",
-        is_available_online=False,
     ),
     "Qwen3VLMoeForConditionalGeneration": _HfExamplesInfo(
         "Qwen/Qwen3-VL-30B-A3B-Instruct",
         max_model_len=4096,
         min_transformers_version="4.57",
-        is_available_online=False,
     ),
     "Qwen3OmniMoeForConditionalGeneration": _HfExamplesInfo(
         "Qwen/Qwen3-Omni-30B-A3B-Instruct",
@@ -799,9 +763,7 @@ _MULTIMODAL_EXAMPLE_MODELS = {
         "Skywork/Skywork-R1V-38B", trust_remote_code=True
     ),
     "SmolVLMForConditionalGeneration": _HfExamplesInfo(
-        "HuggingFaceTB/SmolVLM2-2.2B-Instruct",
-        min_transformers_version="4.56",
-        transformers_version_reason="HF model broken in 4.55",
+        "HuggingFaceTB/SmolVLM2-2.2B-Instruct"
     ),
     "Step3VLForConditionalGeneration": _HfExamplesInfo(
         "stepfun-ai/step3", trust_remote_code=True
@@ -817,7 +779,6 @@ _MULTIMODAL_EXAMPLE_MODELS = {
     ),
     "VoxtralForConditionalGeneration": _HfExamplesInfo(
         "mistralai/Voxtral-Mini-3B-2507",
-        min_transformers_version="4.54",
         # disable this temporarily until we support HF format
         is_available_online=False,
     ),
@@ -878,8 +839,8 @@ _SPECULATIVE_DECODING_EXAMPLE_MODELS = {
     "EagleMiniCPMForCausalLM": _HfExamplesInfo(
         "openbmb/MiniCPM-1B-sft-bf16",
         trust_remote_code=True,
-        is_available_online=False,
         speculative_model="openbmb/MiniCPM-2B-sft-bf16",
+        speculative_method="eagle",
         tokenizer="openbmb/MiniCPM-2B-sft-bf16",
     ),
     "ErnieMTPModel": _HfExamplesInfo(
@@ -890,8 +851,6 @@ _SPECULATIVE_DECODING_EXAMPLE_MODELS = {
     "Glm4MoeMTPModel": _HfExamplesInfo(
         "zai-org/GLM-4.5",
         speculative_model="zai-org/GLM-4.5",
-        min_transformers_version="4.56",
-        is_available_online=False,
     ),
     "LongCatFlashMTPModel": _HfExamplesInfo(
         "meituan-longcat/LongCat-Flash-Chat",

tests/models/test_initialization.py

@@ -105,20 +105,19 @@ def can_initialize(
         if model_arch == "WhisperForConditionalGeneration":
             m.setenv("VLLM_WORKER_MULTIPROC_METHOD", "spawn")
 
-        extra_args = {}
-        if model_arch in ("PrithviGeoSpatialMAE", "Terratorch"):
-            extra_args["enable_mm_embeds"] = True
-
         LLM(
             model_info.default,
             tokenizer=model_info.tokenizer,
             tokenizer_mode=model_info.tokenizer_mode,
             revision=model_info.revision,
             enforce_eager=model_info.enforce_eager,
-            skip_tokenizer_init=model_info.skip_tokenizer_init,
+            skip_tokenizer_init=model_info.require_embed_inputs,
+            enable_prompt_embeds=model_info.require_embed_inputs,
+            enable_mm_embeds=model_info.require_embed_inputs,
             dtype=model_info.dtype,
             speculative_config={
                 "model": model_info.speculative_model,
+                "method": model_info.speculative_method,
                 "num_speculative_tokens": 1,
             }
             if model_info.speculative_model
@@ -133,7 +132,6 @@ def can_initialize(
             else "vllm",
             hf_overrides=hf_overrides_fn,
             max_num_seqs=model_info.max_num_seqs,
-            **extra_args,
         )
 
 

tests/models/utils.py

@@ -309,7 +309,9 @@ def build_model_context(
         limit_mm_per_prompt=limit_mm_per_prompt,
         mm_processor_cache_gb=mm_processor_cache_gb,
         hf_overrides=model_info.hf_overrides,
-        skip_tokenizer_init=model_info.skip_tokenizer_init,
+        skip_tokenizer_init=model_info.require_embed_inputs,
+        enable_prompt_embeds=model_info.require_embed_inputs,
+        enable_mm_embeds=model_info.require_embed_inputs,
         enforce_eager=model_info.enforce_eager,
         **model_config_kwargs,
     )

vllm/model_executor/models/glm4_1v.py

@@ -36,9 +36,7 @@ import torch
 import torch.nn as nn
 import torch.nn.functional as F
 from einops import rearrange
-from packaging.version import Version
 from transformers import BatchFeature
-from transformers import __version__ as TRANSFORMERS_VERSION
 from transformers.models.glm4v.configuration_glm4v import Glm4vVisionConfig
 from transformers.models.glm4v.image_processing_glm4v import (
     Glm4vImageProcessor,
@@ -1270,14 +1268,7 @@ class Glm4vMultiModalProcessor(BaseMultiModalProcessor[Glm4vProcessingInfo]):
                 video_mm_data = dict()
                 video_mm_data["videos"] = [[video_array]]
 
-                # backward compatibility for Transformers 4.55
                 unuse_metadata = ["do_sample_frames"]
-                if (
-                    not hasattr(VideoMetadata, "frames_indices")
-                    and "frames_indices" in metadata
-                ):
-                    unuse_metadata.append("frames_indices")
-
                 video_mm_data["video_metadata"] = [
                     [
                         VideoMetadata(
@@ -1296,24 +1287,11 @@ class Glm4vMultiModalProcessor(BaseMultiModalProcessor[Glm4vProcessingInfo]):
                     mm_kwargs=video_mm_kwargs,
                     tok_kwargs=tok_kwargs,
                 )
-                if not video_mm_kwargs["do_sample_frames"] and Version(
-                    TRANSFORMERS_VERSION
-                ) < Version("4.56.0"):
-                    # Transformers v4.55 has incorrect timestamps issue for
-                    # skip sampling. We construct the placeholder manually to
-                    # get placeholders with correct timestamps.
-                    placeholder = self.info._construct_video_placeholder(
-                        video_array,
-                        metadata,
-                        video_outputs["video_grid_thw"].squeeze(0),
-                    )
-                    video_placeholder = processor.tokenizer.decode(placeholder)
-                else:
-                    input_ids = video_outputs.pop("input_ids")
-                    input_ids[input_ids == processor.image_token_id] = (
-                        processor.video_token_id
-                    )
-                    video_placeholder = processor.tokenizer.batch_decode(input_ids)[0]
+                input_ids = video_outputs.pop("input_ids")
+                input_ids[input_ids == processor.image_token_id] = (
+                    processor.video_token_id
+                )
+                video_placeholder = processor.tokenizer.batch_decode(input_ids)[0]
                 prompt = prompt.replace(
                     "<|begin_of_video|><|video|><|end_of_video|>",
                     video_placeholder,