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[D-FINE] Update names (#37957)

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* Update names

* Fix modular

---------

Co-authored-by: qubvel <qubvel@gmail.com>
This commit is contained in:
NielsRogge
2025-05-05 14:05:46 +02:00
committed by GitHub
parent 2932f318a2
commit 36ca58bf4f
4 changed files with 7 additions and 7 deletions
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2
src/transformers/models/d_fine/configuration_d_fine.py
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@@ -33,7 +33,7 @@ class DFineConfig(PretrainedConfig):
"""
This is the configuration class to store the configuration of a [`DFineModel`]. It is used to instantiate a D-FINE
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
defaults will yield a similar configuration to that of D-FINE-X-COCO "[ustc-community/dfine_x_coco"](https://huggingface.co/ustc-community/dfine_x_coco").
defaults will yield a similar configuration to that of D-FINE-X-COCO "[ustc-community/dfine-xlarge-coco"](https://huggingface.co/ustc-community/dfine-xlarge-coco").
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
documentation from [`PretrainedConfig`] for more information.

4
src/transformers/models/d_fine/modeling_d_fine.py
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@@ -1790,8 +1790,8 @@ class DFineForObjectDetection(DFinePreTrainedModel):
>>> url = "http://images.cocodataset.org/val2017/000000039769.jpg"
>>> image = load_image(url)
>>> image_processor = AutoImageProcessor.from_pretrained("ustc-community/dfine_x_coco")
>>> model = DFineForObjectDetection.from_pretrained("ustc-community/dfine_x_coco")
>>> image_processor = AutoImageProcessor.from_pretrained("ustc-community/dfine-xlarge-coco")
>>> model = DFineForObjectDetection.from_pretrained("ustc-community/dfine-xlarge-coco")
>>> # prepare image for the model
>>> inputs = image_processor(images=image, return_tensors="pt")

6
src/transformers/models/d_fine/modular_d_fine.py
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@@ -52,7 +52,7 @@ class DFineConfig(PretrainedConfig):
"""
This is the configuration class to store the configuration of a [`DFineModel`]. It is used to instantiate a D-FINE
model according to the specified arguments, defining the model architecture. Instantiating a configuration with the
defaults will yield a similar configuration to that of D-FINE-X-COCO "[ustc-community/dfine_x_coco"](https://huggingface.co/ustc-community/dfine_x_coco").
defaults will yield a similar configuration to that of D-FINE-X-COCO "[ustc-community/dfine-xlarge-coco"](https://huggingface.co/ustc-community/dfine-xlarge-coco").
Configuration objects inherit from [`PretrainedConfig`] and can be used to control the model outputs. Read the
documentation from [`PretrainedConfig`] for more information.
@@ -922,8 +922,8 @@ class DFineForObjectDetection(RTDetrForObjectDetection, DFinePreTrainedModel):
>>> url = "http://images.cocodataset.org/val2017/000000039769.jpg"
>>> image = load_image(url)
>>> image_processor = AutoImageProcessor.from_pretrained("ustc-community/dfine_x_coco")
>>> model = DFineForObjectDetection.from_pretrained("ustc-community/dfine_x_coco")
>>> image_processor = AutoImageProcessor.from_pretrained("ustc-community/dfine-xlarge-coco")
>>> model = DFineForObjectDetection.from_pretrained("ustc-community/dfine-xlarge-coco")
>>> # prepare image for the model
>>> inputs = image_processor(images=image, return_tensors="pt")

2
tests/models/d_fine/test_modeling_d_fine.py
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@@ -46,7 +46,7 @@ from ...test_modeling_common import ModelTesterMixin, _config_zero_init, floats_
from ...test_pipeline_mixin import PipelineTesterMixin
CHECKPOINT = "ustc-community/dfine_s_coco"
CHECKPOINT = "ustc-community/dfine-small-coco"
class DFineModelTester: