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zeromodels / resnet50_gluon_in1k
Model's Last Updated: August 30 2026
image-classification
Introduction of resnet50_gluon_in1k
Model Details of resnet50_gluon_in1k
See our collection for all versions of ResNet.
Run ResNet with Keras 3: JAX, PyTorch, or TensorFlow
kerasformers/resnet50_gluon_in1k
Paper: Deep Residual Learning for Image Recognition (arXiv:1512.03385) · HF Papers
ResNet is the residual CNN backbone that introduced skip connections. Use
ResNetImageClassify
for ImageNet logits or
ResNetModel
(optionally
as_backbone=True
) for feature maps.
For more details on the model, please go to the upstream model card .
Pure-
Keras 3
conversion of
timm/resnet50.gluon_in1k
for
kerasformers
. One implementation runs unmodified on
TensorFlow / Torch / JAX
.
This is an
image-classification / backbone
checkpoint (
ResNetImageClassify
/
ResNetModel
).
✨ Quick start
import os
os.environ["KERAS_BACKEND"] = "torch" # or "jax" / "tensorflow"
from PIL import Image
import numpy as np
from kerasformers.models.resnet import ResNetImageClassify, ResNetModel
model = ResNetImageClassify.from_weights("kerasformers/resnet50_gluon_in1k")
backbone = ResNetModel.from_weights(
"kerasformers/resnet50_gluon_in1k", as_backbone=True
)
image = Image.open("your_image.jpg").convert("RGB")
image = image.resize((224, 224))
x = np.asarray(image, dtype="float32")[None] # (1, H, W, 3)
print(model(x).shape) # (1, num_classes)
feats = backbone(x)
print(len(feats), [tuple(f.shape) for f in feats])
Load any ResNet variant the same way with
from_weights("kerasformers/<variant>")
:
| Variant | Hub |
|---|---|
resnet101_a1_in1k
|
kerasformers/resnet101_a1_in1k
|
resnet101_gluon_in1k
|
kerasformers/resnet101_gluon_in1k
|
resnet101_tv_in1k
|
kerasformers/resnet101_tv_in1k
|
resnet152_a1_in1k
|
kerasformers/resnet152_a1_in1k
|
resnet152_gluon_in1k
|
kerasformers/resnet152_gluon_in1k
|
resnet152_tv_in1k
|
kerasformers/resnet152_tv_in1k
|
resnet50_a1_in1k
|
kerasformers/resnet50_a1_in1k
|
resnet50_gluon_in1k
|
kerasformers/resnet50_gluon_in1k
|
resnet50_tv_in1k
|
kerasformers/resnet50_tv_in1k
|
Tips
-
Set
KERAS_BACKENDbefore importing Keras / kerasformers. -
ResNetImageClassifyreturns class logits;ResNetModelreturns features (as_backbone=Truefor multi-scale stages). - See docs and Loading Weights .
-
Upstream / timm checkpoints:
ResNetImageClassify.from_weights("hf:timm/resnet50.gluon_in1k").
Special Thanks
A huge thank you to the ResNet authors and the timm / Hub communities for creating and releasing these models.
License: see YAML
license
(usually matches the upstream checkpoint).
Runs of zeromodels resnet50_gluon_in1k on huggingface.co
49
Total runs
0
24-hour runs
-2
3-day runs
9
7-day runs
11
30-day runs
More Information About resnet50_gluon_in1k huggingface.co Model
Url of resnet50_gluon_in1k
resnet50_gluon_in1k huggingface.co Url
Provider of resnet50_gluon_in1k huggingface.co
Other API from zeromodels
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