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[CI/Build] Bump transformers version (#27528)

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Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>
Signed-off-by: Isotr0py <mozf@mail2.sysu.edu.cn>
Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
Co-authored-by: Isotr0py <mozf@mail2.sysu.edu.cn>
Co-authored-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Cyrus Leung
2025-11-01 13:11:07 +08:00
committed by GitHub
parent 29de3cdee4
commit 879a06579e
9 changed files with 17 additions and 17 deletions
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2
requirements/common.txt
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@@ -7,7 +7,7 @@ requests >= 2.26.0
tqdm tqdm
blake3 blake3
py-cpuinfo py-cpuinfo
transformers >= 4.56.0 transformers >= 4.56.0, < 5
tokenizers >= 0.21.1 # Required for fast incremental detokenization. tokenizers >= 0.21.1 # Required for fast incremental detokenization.
protobuf # Required by LlamaTokenizer. protobuf # Required by LlamaTokenizer.
fastapi[standard] >= 0.115.0 # Required by FastAPI's form models in the OpenAI API server's audio transcriptions endpoint. fastapi[standard] >= 0.115.0 # Required by FastAPI's form models in the OpenAI API server's audio transcriptions endpoint.

2
requirements/nightly_torch_test.txt
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@@ -29,7 +29,7 @@ opencv-python-headless >= 4.11.0 # required for video test
datamodel_code_generator # required for minicpm3 test datamodel_code_generator # required for minicpm3 test
lm-eval[api] @ git+https://github.com/EleutherAI/lm-evaluation-harness.git@206b7722158f58c35b7ffcd53b035fdbdda5126d # required for model evaluation test lm-eval[api] @ git+https://github.com/EleutherAI/lm-evaluation-harness.git@206b7722158f58c35b7ffcd53b035fdbdda5126d # required for model evaluation test
mteb>=1.38.11, <2 # required for mteb test mteb>=1.38.11, <2 # required for mteb test
transformers==4.56.2 transformers==4.57.1
tokenizers==0.22.0 tokenizers==0.22.0
schemathesis>=3.39.15 # Required for openai schema test. schemathesis>=3.39.15 # Required for openai schema test.
# quantization # quantization

2
requirements/test.in
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@@ -37,7 +37,7 @@ datamodel_code_generator # required for minicpm3 test
# TODO: Use lm-eval[api]==0.4.10 once released # TODO: Use lm-eval[api]==0.4.10 once released
lm-eval[api] @ git+https://github.com/EleutherAI/lm-evaluation-harness.git@206b7722158f58c35b7ffcd53b035fdbdda5126d # required for model evaluation test lm-eval[api] @ git+https://github.com/EleutherAI/lm-evaluation-harness.git@206b7722158f58c35b7ffcd53b035fdbdda5126d # required for model evaluation test
mteb[bm25s]>=1.38.11, <2 # required for mteb test mteb[bm25s]>=1.38.11, <2 # required for mteb test
transformers==4.56.2 transformers==4.57.1
tokenizers==0.22.0 tokenizers==0.22.0
schemathesis>=3.39.15 # Required for openai schema test. schemathesis>=3.39.15 # Required for openai schema test.
# quantization # quantization

2
requirements/test.txt
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@@ -1196,7 +1196,7 @@ tqdm==4.66.6
# transformers # transformers
tqdm-multiprocess==0.0.11 tqdm-multiprocess==0.0.11
# via lm-eval # via lm-eval
transformers==4.56.2 transformers==4.57.1
# via # via
# -r requirements/test.in # -r requirements/test.in
# genai-perf # genai-perf

2
tests/models/multimodal/generation/test_maverick.py
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@@ -186,6 +186,8 @@ def create_reduced_config(
if "text_config" in config_dict: if "text_config" in config_dict:
original_text_layers = config_dict["text_config"]["num_hidden_layers"] original_text_layers = config_dict["text_config"]["num_hidden_layers"]
config_dict["text_config"]["num_hidden_layers"] = text_layers config_dict["text_config"]["num_hidden_layers"] = text_layers
original_layer_types = config_dict["text_config"]["layer_types"]
config_dict["text_config"]["layer_types"] = original_layer_types[:text_layers]
print(f"Reduced text layers from {original_text_layers} to {text_layers}") print(f"Reduced text layers from {original_text_layers} to {text_layers}")
original_num_experts = config_dict["text_config"]["num_local_experts"] original_num_experts = config_dict["text_config"]["num_local_experts"]

12
tests/models/registry.py
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@@ -882,27 +882,27 @@ _SPECULATIVE_DECODING_EXAMPLE_MODELS = {
_TRANSFORMERS_BACKEND_MODELS = { _TRANSFORMERS_BACKEND_MODELS = {
"TransformersEmbeddingModel": _HfExamplesInfo( "TransformersEmbeddingModel": _HfExamplesInfo(
"BAAI/bge-base-en-v1.5", min_transformers_version="4.57.0.dev0" "BAAI/bge-base-en-v1.5", min_transformers_version="5.0.0"
), ),
"TransformersForSequenceClassification": _HfExamplesInfo( "TransformersForSequenceClassification": _HfExamplesInfo(
"papluca/xlm-roberta-base-language-detection", "papluca/xlm-roberta-base-language-detection",
min_transformers_version="4.57.0.dev0", min_transformers_version="5.0.0",
), ),
"TransformersForCausalLM": _HfExamplesInfo( "TransformersForCausalLM": _HfExamplesInfo(
"hmellor/Ilama-3.2-1B", trust_remote_code=True "hmellor/Ilama-3.2-1B", trust_remote_code=True
), ),
"TransformersMultiModalForCausalLM": _HfExamplesInfo("BAAI/Emu3-Chat-hf"), "TransformersMultiModalForCausalLM": _HfExamplesInfo("BAAI/Emu3-Chat-hf"),
"TransformersMoEForCausalLM": _HfExamplesInfo( "TransformersMoEForCausalLM": _HfExamplesInfo(
"allenai/OLMoE-1B-7B-0924", min_transformers_version="4.57.0.dev0" "allenai/OLMoE-1B-7B-0924", min_transformers_version="5.0.0"
), ),
"TransformersMultiModalMoEForCausalLM": _HfExamplesInfo( "TransformersMultiModalMoEForCausalLM": _HfExamplesInfo(
"Qwen/Qwen3-VL-30B-A3B-Instruct", min_transformers_version="4.57.0.dev0" "Qwen/Qwen3-VL-30B-A3B-Instruct", min_transformers_version="5.0.0"
), ),
"TransformersMoEEmbeddingModel": _HfExamplesInfo( "TransformersMoEEmbeddingModel": _HfExamplesInfo(
"Qwen/Qwen3-30B-A3B", min_transformers_version="4.57.0.dev0" "Qwen/Qwen3-30B-A3B", min_transformers_version="5.0.0"
), ),
"TransformersMoEForSequenceClassification": _HfExamplesInfo( "TransformersMoEForSequenceClassification": _HfExamplesInfo(
"Qwen/Qwen3-30B-A3B", min_transformers_version="4.57.0.dev0" "Qwen/Qwen3-30B-A3B", min_transformers_version="5.0.0"
), ),
"TransformersMultiModalEmbeddingModel": _HfExamplesInfo("google/gemma-3-4b-it"), "TransformersMultiModalEmbeddingModel": _HfExamplesInfo("google/gemma-3-4b-it"),
"TransformersMultiModalForSequenceClassification": _HfExamplesInfo( "TransformersMultiModalForSequenceClassification": _HfExamplesInfo(

2
tests/models/test_transformers.py
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@@ -82,7 +82,7 @@ def test_models(
from packaging.version import Version from packaging.version import Version
installed = Version(transformers.__version__) installed = Version(transformers.__version__)
required = Version("4.57.0.dev0") required = Version("5.0.0")
if model == "allenai/OLMoE-1B-7B-0924" and installed < required: if model == "allenai/OLMoE-1B-7B-0924" and installed < required:
pytest.skip( pytest.skip(
"MoE models with the Transformers backend require " "MoE models with the Transformers backend require "

4
vllm/model_executor/models/moonvit.py
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@@ -49,7 +49,7 @@ from functools import cached_property
import torch import torch
import torch.nn as nn import torch.nn as nn
import torch.nn.functional as F import torch.nn.functional as F
from transformers.activations import ACT2FN, PytorchGELUTanh from transformers.activations import ACT2FN
from transformers.modeling_utils import PreTrainedModel from transformers.modeling_utils import PreTrainedModel
from transformers.utils import is_flash_attn_2_available from transformers.utils import is_flash_attn_2_available
@@ -651,7 +651,7 @@ class MoonVitPretrainedModel(PreTrainedModel):
"num_heads": config.num_attention_heads, "num_heads": config.num_attention_heads,
"hidden_dim": config.hidden_size, "hidden_dim": config.hidden_size,
"mlp_dim": config.intermediate_size, "mlp_dim": config.intermediate_size,
"activation": PytorchGELUTanh(), "activation": ACT2FN["gelu_pytorch_tanh"],
"attn_bias": True, "attn_bias": True,
"attn_implementation": config._attn_implementation, "attn_implementation": config._attn_implementation,
}, },

6
vllm/model_executor/models/qwen2_vl.py
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@@ -34,7 +34,7 @@ import torch
import torch.nn as nn import torch.nn as nn
import torch.nn.functional as F import torch.nn.functional as F
from einops import rearrange, repeat from einops import rearrange, repeat
from transformers import AutoConfig, BatchFeature, PretrainedConfig from transformers import BatchFeature, PretrainedConfig
from transformers.models.qwen2_vl import Qwen2VLImageProcessor, Qwen2VLProcessor from transformers.models.qwen2_vl import Qwen2VLImageProcessor, Qwen2VLProcessor
from transformers.models.qwen2_vl.configuration_qwen2_vl import ( from transformers.models.qwen2_vl.configuration_qwen2_vl import (
Qwen2VLConfig, Qwen2VLConfig,
@@ -1651,9 +1651,7 @@ class Tarsier2Processor(Qwen2VLProcessor):
class Tarsier2ProcessingInfo(Qwen2VLProcessingInfo): class Tarsier2ProcessingInfo(Qwen2VLProcessingInfo):
def get_hf_config(self) -> Qwen2VLConfig: def get_hf_config(self) -> Qwen2VLConfig:
model_path = self.ctx.model_config.model model_path = self.ctx.model_config.model
original_config = AutoConfig.from_pretrained(model_path) correct_config = Qwen2VLConfig.from_pretrained(model_path)
config_dict = original_config.to_dict()
correct_config = Qwen2VLConfig.from_dict(config_dict)
return correct_config return correct_config