Install transformers from main for doc and staging (#13723)

* Use Mistral3Model/Ministral3ForCausalLM

* [docs] add magcache to caching api listing (#13714)

add magcache to caching api listing

* install transformers from main

* up

* up

* up

* up[

* shorten deprecation cycle for flax.

* Revert "shorten deprecation cycle for flax."

This reverts commit 692d98db7b.

---------

Co-authored-by: Akshan Krithick <akshankrithick305@gmail.com>
Co-authored-by: YiYi Xu <yixu310@gmail.com>

.github/workflows/build_documentation.yml

@@ -25,6 +25,7 @@ jobs:
       notebook_folder: diffusers_doc
       languages: en ko zh ja pt
       custom_container: diffusers/diffusers-doc-builder
+      pre_command: uv pip uninstall transformers huggingface_hub && UV_PRERELEASE=allow uv pip install -U transformers@git+https://github.com/huggingface/transformers.git
     secrets:
       token: ${{ secrets.HUGGINGFACE_PUSH }}
       hf_token: ${{ secrets.HF_DOC_BUILD_PUSH }}

.github/workflows/build_pr_documentation.yml

@@ -50,3 +50,4 @@ jobs:
       package: diffusers
       languages: en ko zh ja pt
       custom_container: diffusers/diffusers-doc-builder
+      pre_command: uv pip uninstall transformers huggingface_hub && UV_PRERELEASE=allow uv pip install -U transformers@git+https://github.com/huggingface/transformers.git

.github/workflows/pr_tests.yml

@@ -194,6 +194,8 @@ jobs:
     - name: Install dependencies
       run: |
         uv pip install -e ".[quality]"
+        uv pip uninstall transformers huggingface_hub && UV_PRERELEASE=allow uv pip install -U transformers@git+https://github.com/huggingface/transformers.git
+        uv pip uninstall tokenizers && uv pip install "tokenizers<=0.23.0"
 
     - name: Environment
       run: |

src/diffusers/__init__.py

@@ -22,6 +22,7 @@ from .utils import (
     is_torchao_available,
     is_torchsde_available,
     is_transformers_available,
+    is_transformers_flax_compatible,
     is_transformers_version,
 )
 
@@ -861,7 +862,6 @@ else:
     _import_structure["models.modeling_flax_utils"] = ["FlaxModelMixin"]
     _import_structure["models.unets.unet_2d_condition_flax"] = ["FlaxUNet2DConditionModel"]
     _import_structure["models.vae_flax"] = ["FlaxAutoencoderKL"]
-    _import_structure["pipelines"].extend(["FlaxDiffusionPipeline"])
     _import_structure["schedulers"].extend(
         [
             "FlaxDDIMScheduler",
@@ -878,7 +878,7 @@ else:
 
 
 try:
-    if not (is_flax_available() and is_transformers_available()):
+    if not (is_flax_available() and is_transformers_available() and is_transformers_flax_compatible()):
         raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
     from .utils import dummy_flax_and_transformers_objects  # noqa F403
@@ -891,6 +891,7 @@ except OptionalDependencyNotAvailable:
 else:
     _import_structure["pipelines"].extend(
         [
+            "FlaxDiffusionPipeline",
             "FlaxStableDiffusionControlNetPipeline",
             "FlaxStableDiffusionImg2ImgPipeline",
             "FlaxStableDiffusionInpaintPipeline",
@@ -1620,7 +1621,6 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
         from .models.modeling_flax_utils import FlaxModelMixin
         from .models.unets.unet_2d_condition_flax import FlaxUNet2DConditionModel
         from .models.vae_flax import FlaxAutoencoderKL
-        from .pipelines import FlaxDiffusionPipeline
         from .schedulers import (
             FlaxDDIMScheduler,
             FlaxDDPMScheduler,
@@ -1634,12 +1634,13 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
         )
 
     try:
-        if not (is_flax_available() and is_transformers_available()):
+        if not (is_flax_available() and is_transformers_available() and is_transformers_flax_compatible()):
             raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
         from .utils.dummy_flax_and_transformers_objects import *  # noqa F403
     else:
         from .pipelines import (
+            FlaxDiffusionPipeline,
             FlaxStableDiffusionControlNetPipeline,
             FlaxStableDiffusionImg2ImgPipeline,
             FlaxStableDiffusionInpaintPipeline,

src/diffusers/modular_pipelines/ernie_image/encoders.py

@@ -15,16 +15,23 @@
 import json
 
 import torch
-from transformers import AutoModel, AutoModelForCausalLM, AutoTokenizer
+from transformers import AutoTokenizer, Mistral3Model
 
 from ...configuration_utils import FrozenDict
 from ...guiders import ClassifierFreeGuidance
 from ...utils import logging
+from ...utils.import_utils import is_transformers_version
 from ..modular_pipeline import ModularPipelineBlocks, PipelineState
 from ..modular_pipeline_utils import ComponentSpec, InputParam, OutputParam
 from .modular_pipeline import ErnieImageModularPipeline
 
 
+if is_transformers_version("<", "5.0.0"):
+    raise ImportError("`ErnieImageModularPipeline` requires `transformers>=5.0.0` for `Ministral3ForCausalLM`.")
+
+from transformers import Ministral3ForCausalLM  # noqa: E402
+
+
 logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
 
@@ -38,7 +45,7 @@ class ErnieImagePromptEnhancerStep(ModularPipelineBlocks):
     @property
     def expected_components(self) -> list[ComponentSpec]:
         return [
-            ComponentSpec("pe", AutoModelForCausalLM),
+            ComponentSpec("pe", Ministral3ForCausalLM),
             ComponentSpec("pe_tokenizer", AutoTokenizer),
         ]
 
@@ -83,7 +90,7 @@ class ErnieImagePromptEnhancerStep(ModularPipelineBlocks):
 
     @staticmethod
     def _enhance_prompt(
-        pe: AutoModelForCausalLM,
+        pe: Ministral3ForCausalLM,
         pe_tokenizer: AutoTokenizer,
         prompt: str,
         device: torch.device,
@@ -160,7 +167,7 @@ class ErnieImageTextEncoderStep(ModularPipelineBlocks):
     @property
     def expected_components(self) -> list[ComponentSpec]:
         return [
-            ComponentSpec("text_encoder", AutoModel),
+            ComponentSpec("text_encoder", Mistral3Model),
             ComponentSpec("tokenizer", AutoTokenizer),
             ComponentSpec(
                 "guider",
@@ -200,7 +207,7 @@ class ErnieImageTextEncoderStep(ModularPipelineBlocks):
 
     @staticmethod
     def _encode(
-        text_encoder: AutoModel,
+        text_encoder: Mistral3Model,
         tokenizer: AutoTokenizer,
         prompt: list[str],
         device: torch.device,

src/diffusers/pipelines/__init__.py

@@ -5,7 +5,6 @@ from ..utils import (
     OptionalDependencyNotAvailable,
     _LazyModule,
     get_objects_from_module,
-    is_flax_available,
     is_librosa_available,
     is_note_seq_available,
     is_onnx_available,
@@ -14,6 +13,7 @@ from ..utils import (
     is_torch_available,
     is_torch_npu_available,
     is_transformers_available,
+    is_transformers_flax_compatible,
     is_transformers_version,
 )
 
@@ -504,7 +504,7 @@ else:
     _import_structure["consisid"] = ["ConsisIDPipeline"]
 
 try:
-    if not is_flax_available():
+    if not is_transformers_flax_compatible():
         raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
     from ..utils import dummy_flax_objects  # noqa F403
@@ -513,7 +513,7 @@ except OptionalDependencyNotAvailable:
 else:
     _import_structure["pipeline_flax_utils"] = ["FlaxDiffusionPipeline"]
 try:
-    if not (is_flax_available() and is_transformers_available()):
+    if not is_transformers_flax_compatible():
         raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
     from ..utils import dummy_flax_and_transformers_objects  # noqa F403
@@ -930,7 +930,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
             from .consisid import ConsisIDPipeline
 
         try:
-            if not is_flax_available():
+            if not is_transformers_flax_compatible():
                 raise OptionalDependencyNotAvailable()
         except OptionalDependencyNotAvailable:
             from ..utils.dummy_flax_objects import *  # noqa F403
@@ -938,7 +938,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
             from .pipeline_flax_utils import FlaxDiffusionPipeline
 
         try:
-            if not (is_flax_available() and is_transformers_available()):
+            if not is_transformers_flax_compatible():
                 raise OptionalDependencyNotAvailable()
         except OptionalDependencyNotAvailable:
             from ..utils.dummy_flax_and_transformers_objects import *

src/diffusers/pipelines/controlnet/__init__.py

@@ -5,9 +5,9 @@ from ...utils import (
     OptionalDependencyNotAvailable,
     _LazyModule,
     get_objects_from_module,
-    is_flax_available,
     is_torch_available,
     is_transformers_available,
+    is_transformers_flax_compatible,
 )
 
 
@@ -34,7 +34,7 @@ else:
     _import_structure["pipeline_controlnet_union_sd_xl"] = ["StableDiffusionXLControlNetUnionPipeline"]
     _import_structure["pipeline_controlnet_union_sd_xl_img2img"] = ["StableDiffusionXLControlNetUnionImg2ImgPipeline"]
 try:
-    if not (is_transformers_available() and is_flax_available()):
+    if not is_transformers_flax_compatible():
         raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
     from ...utils import dummy_flax_and_transformers_objects  # noqa F403
@@ -65,7 +65,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
         from .pipeline_controlnet_union_sd_xl_img2img import StableDiffusionXLControlNetUnionImg2ImgPipeline
 
     try:
-        if not (is_transformers_available() and is_flax_available()):
+        if not is_transformers_flax_compatible():
             raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
         from ...utils.dummy_flax_and_transformers_objects import *  # noqa F403

src/diffusers/pipelines/controlnet_sd3/__init__.py

@@ -5,9 +5,9 @@ from ...utils import (
     OptionalDependencyNotAvailable,
     _LazyModule,
     get_objects_from_module,
-    is_flax_available,
     is_torch_available,
     is_transformers_available,
+    is_transformers_flax_compatible,
 )
 
 
@@ -39,7 +39,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
         from .pipeline_stable_diffusion_3_controlnet_inpainting import StableDiffusion3ControlNetInpaintingPipeline
 
     try:
-        if not (is_transformers_available() and is_flax_available()):
+        if not is_transformers_flax_compatible():
             raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
         from ...utils.dummy_flax_and_transformers_objects import *  # noqa F403

src/diffusers/pipelines/deprecated/controlnet_xs/__init__.py

@@ -5,9 +5,9 @@ from ....utils import (
     OptionalDependencyNotAvailable,
     _LazyModule,
     get_objects_from_module,
-    is_flax_available,
     is_torch_available,
     is_transformers_available,
+    is_transformers_flax_compatible,
 )
 
 
@@ -25,7 +25,7 @@ else:
     _import_structure["pipeline_controlnet_xs"] = ["StableDiffusionControlNetXSPipeline"]
     _import_structure["pipeline_controlnet_xs_sd_xl"] = ["StableDiffusionXLControlNetXSPipeline"]
 try:
-    if not (is_transformers_available() and is_flax_available()):
+    if not is_transformers_flax_compatible():
         raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
     from ....utils import dummy_flax_and_transformers_objects  # noqa F403
@@ -47,7 +47,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
         from .pipeline_controlnet_xs_sd_xl import StableDiffusionXLControlNetXSPipeline
 
     try:
-        if not (is_transformers_available() and is_flax_available()):
+        if not is_transformers_flax_compatible():
             raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
         from ....utils.dummy_flax_and_transformers_objects import *  # noqa F403

src/diffusers/pipelines/ernie_image/pipeline_ernie_image.py

@@ -20,7 +20,7 @@ import json
 from typing import Callable, List, Optional, Union
 
 import torch
-from transformers import AutoModel, AutoModelForCausalLM, AutoTokenizer
+from transformers import AutoTokenizer, Mistral3Model
 
 from ...image_processor import VaeImageProcessor
 from ...loaders import ErnieImageLoraLoaderMixin
@@ -28,10 +28,17 @@ from ...models import AutoencoderKLFlux2
 from ...models.transformers import ErnieImageTransformer2DModel
 from ...pipelines.pipeline_utils import DiffusionPipeline
 from ...schedulers import FlowMatchEulerDiscreteScheduler
+from ...utils.import_utils import is_transformers_version
 from ...utils.torch_utils import randn_tensor
 from .pipeline_output import ErnieImagePipelineOutput
 
 
+if is_transformers_version("<", "5.0.0"):
+    raise ImportError("`ErnieImagePipeline` requires `transformers>=5.0.0` for `Ministral3ForCausalLM`.")
+
+from transformers import Ministral3ForCausalLM  # noqa: E402
+
+
 class ErnieImagePipeline(DiffusionPipeline, ErnieImageLoraLoaderMixin):
     """
     Pipeline for text-to-image generation using ErnieImageTransformer2DModel.
@@ -52,10 +59,10 @@ class ErnieImagePipeline(DiffusionPipeline, ErnieImageLoraLoaderMixin):
         self,
         transformer: ErnieImageTransformer2DModel,
         vae: AutoencoderKLFlux2,
-        text_encoder: AutoModel,
+        text_encoder: Mistral3Model,
         tokenizer: AutoTokenizer,
         scheduler: FlowMatchEulerDiscreteScheduler,
-        pe: Optional[AutoModelForCausalLM] = None,
+        pe: Optional[Ministral3ForCausalLM] = None,
         pe_tokenizer: Optional[AutoTokenizer] = None,
     ):
         super().__init__()

src/diffusers/pipelines/pipeline_flax_utils.py

@@ -36,12 +36,12 @@ from ..utils import (
     BaseOutput,
     PushToHubMixin,
     http_user_agent,
-    is_transformers_available,
+    is_transformers_flax_compatible,
     logging,
 )
 
 
-if is_transformers_available():
+if is_transformers_flax_compatible():
     from transformers import FlaxPreTrainedModel
 
 INDEX_FILE = "diffusion_flax_model.bin"
@@ -501,7 +501,7 @@ class FlaxDiffusionPipeline(ConfigMixin, PushToHubMixin):
                         dtype=dtype,
                     )
                     params[name] = loaded_params
-                elif is_transformers_available() and issubclass(class_obj, FlaxPreTrainedModel):
+                elif is_transformers_flax_compatible() and issubclass(class_obj, FlaxPreTrainedModel):
                     if from_pt:
                         # TODO(Suraj): Fix this in Transformers. We should be able to use `_do_init=False` here
                         loaded_sub_model = load_method(loadable_folder, from_pt=from_pt)

src/diffusers/pipelines/stable_diffusion/__init__.py

@@ -5,10 +5,10 @@ from ...utils import (
     OptionalDependencyNotAvailable,
     _LazyModule,
     get_objects_from_module,
-    is_flax_available,
     is_onnx_available,
     is_torch_available,
     is_transformers_available,
+    is_transformers_flax_compatible,
     is_transformers_version,
 )
 
@@ -17,7 +17,7 @@ _dummy_objects = {}
 _additional_imports = {}
 _import_structure = {"pipeline_output": ["StableDiffusionPipelineOutput"]}
 
-if is_transformers_available() and is_flax_available():
+if is_transformers_flax_compatible():
     _import_structure["pipeline_output"].extend(["FlaxStableDiffusionPipelineOutput"])
 try:
     if not (is_transformers_available() and is_torch_available()):
@@ -82,7 +82,7 @@ else:
     _import_structure["pipeline_onnx_stable_diffusion_inpaint_legacy"] = ["OnnxStableDiffusionInpaintPipelineLegacy"]
     _import_structure["pipeline_onnx_stable_diffusion_upscale"] = ["OnnxStableDiffusionUpscalePipeline"]
 
-if is_transformers_available() and is_flax_available():
+if is_transformers_flax_compatible():
     from ...schedulers.scheduling_pndm_flax import PNDMSchedulerState
 
     _additional_imports.update({"PNDMSchedulerState": PNDMSchedulerState})
@@ -162,7 +162,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
         )
 
     try:
-        if not (is_transformers_available() and is_flax_available()):
+        if not is_transformers_flax_compatible():
             raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
         from ...utils.dummy_flax_objects import *

src/diffusers/pipelines/stable_diffusion_xl/__init__.py

@@ -5,9 +5,9 @@ from ...utils import (
     OptionalDependencyNotAvailable,
     _LazyModule,
     get_objects_from_module,
-    is_flax_available,
     is_torch_available,
     is_transformers_available,
+    is_transformers_flax_compatible,
 )
 
 
@@ -15,7 +15,7 @@ _dummy_objects = {}
 _additional_imports = {}
 _import_structure = {"pipeline_output": ["StableDiffusionXLPipelineOutput"]}
 
-if is_transformers_available() and is_flax_available():
+if is_transformers_flax_compatible():
     _import_structure["pipeline_output"].extend(["FlaxStableDiffusionXLPipelineOutput"])
 try:
     if not (is_transformers_available() and is_torch_available()):
@@ -30,7 +30,7 @@ else:
     _import_structure["pipeline_stable_diffusion_xl_inpaint"] = ["StableDiffusionXLInpaintPipeline"]
     _import_structure["pipeline_stable_diffusion_xl_instruct_pix2pix"] = ["StableDiffusionXLInstructPix2PixPipeline"]
 
-if is_transformers_available() and is_flax_available():
+if is_transformers_flax_compatible():
     from ...schedulers.scheduling_pndm_flax import PNDMSchedulerState
 
     _additional_imports.update({"PNDMSchedulerState": PNDMSchedulerState})
@@ -50,7 +50,7 @@ if TYPE_CHECKING or DIFFUSERS_SLOW_IMPORT:
         from .pipeline_stable_diffusion_xl_instruct_pix2pix import StableDiffusionXLInstructPix2PixPipeline
 
     try:
-        if not (is_transformers_available() and is_flax_available()):
+        if not is_transformers_flax_compatible():
             raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
         from ...utils.dummy_flax_objects import *

src/diffusers/utils/__init__.py

@@ -122,6 +122,7 @@ from .import_utils import (
     is_torchsde_available,
     is_torchvision_available,
     is_transformers_available,
+    is_transformers_flax_compatible,
     is_transformers_version,
     is_unidecode_available,
     is_wandb_available,

src/diffusers/utils/dummy_flax_and_transformers_objects.py

@@ -2,6 +2,21 @@
 from ..utils import DummyObject, requires_backends
 
 
+class FlaxDiffusionPipeline(metaclass=DummyObject):
+    _backends = ["flax", "transformers"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["flax", "transformers"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["flax", "transformers"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["flax", "transformers"])
+
+
 class FlaxStableDiffusionControlNetPipeline(metaclass=DummyObject):
     _backends = ["flax", "transformers"]
 

src/diffusers/utils/dummy_flax_objects.py

@@ -62,21 +62,6 @@ class FlaxAutoencoderKL(metaclass=DummyObject):
         requires_backends(cls, ["flax"])
 
 
-class FlaxDiffusionPipeline(metaclass=DummyObject):
-    _backends = ["flax"]
-
-    def __init__(self, *args, **kwargs):
-        requires_backends(self, ["flax"])
-
-    @classmethod
-    def from_config(cls, *args, **kwargs):
-        requires_backends(cls, ["flax"])
-
-    @classmethod
-    def from_pretrained(cls, *args, **kwargs):
-        requires_backends(cls, ["flax"])
-
-
 class FlaxDDIMScheduler(metaclass=DummyObject):
     _backends = ["flax"]
 

src/diffusers/utils/dummy_transformers_flax_objects.py

@@ -0,0 +1,92 @@
+# This file is autogenerated by the command `make fix-copies`, do not edit.
+from ..utils import DummyObject, requires_backends
+
+
+class FlaxDiffusionPipeline(metaclass=DummyObject):
+    _backends = ["transformers_flax"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["transformers_flax"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["transformers_flax"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["transformers_flax"])
+
+
+class FlaxStableDiffusionControlNetPipeline(metaclass=DummyObject):
+    _backends = ["transformers_flax"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["transformers_flax"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["transformers_flax"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["transformers_flax"])
+
+
+class FlaxStableDiffusionImg2ImgPipeline(metaclass=DummyObject):
+    _backends = ["transformers_flax"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["transformers_flax"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["transformers_flax"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["transformers_flax"])
+
+
+class FlaxStableDiffusionInpaintPipeline(metaclass=DummyObject):
+    _backends = ["transformers_flax"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["transformers_flax"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["transformers_flax"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["transformers_flax"])
+
+
+class FlaxStableDiffusionPipeline(metaclass=DummyObject):
+    _backends = ["transformers_flax"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["transformers_flax"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["transformers_flax"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["transformers_flax"])
+
+
+class FlaxStableDiffusionXLPipeline(metaclass=DummyObject):
+    _backends = ["transformers_flax"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["transformers_flax"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["transformers_flax"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["transformers_flax"])

src/diffusers/utils/import_utils.py

@@ -258,6 +258,22 @@ def is_transformers_available():
     return _transformers_available
 
 
+def is_transformers_flax_compatible():
+    # Flax classes (e.g. FlaxCLIPTextModel, FlaxPreTrainedModel) were removed from
+    # transformers main on the path to its v5 release. Gate Flax pipeline registration
+    # on transformers still shipping them so `import diffusers` doesn't crash.
+    # Name avoids the `is_*_available()` pattern so utils/check_dummies.py keeps
+    # generating the `flax_and_transformers` backend group when this is combined with
+    # the legacy is_flax_available()/is_transformers_available() pair.
+    if not (_transformers_available and _flax_available):
+        return False
+    try:
+        import transformers
+    except ImportError:
+        return False
+    return hasattr(transformers, "FlaxPreTrainedModel")
+
+
 def is_inflect_available():
     return _inflect_available