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Sponsored by
YouArt
zeromodels / inception_next_base_sail_in1k
Model's Last Updated: August 30 2026
image-classification
Introduction of inception_next_base_sail_in1k
Model Details of inception_next_base_sail_in1k
See our collection for all versions of InceptionNeXt.
Run InceptionNeXt with Keras 3: JAX, PyTorch, or TensorFlow
kerasformers/inception_next_base_sail_in1k
Paper: InceptionNeXt: When Inception Meets ConvNeXt (arXiv:2303.16900) · HF Papers
InceptionNeXt blends Inception-style token mixing with a ConvNeXt meta-architecture for efficient ImageNet classification.
For more details on the model, please go to the upstream model card .
Pure-
Keras 3
conversion of
timm/inception_next_base.sail_in1k
for
kerasformers
. One implementation runs unmodified on
TensorFlow / Torch / JAX
.
This is an
image-classification / backbone
checkpoint (
InceptionNextImageClassify
/
InceptionNextModel
).
✨ Quick start
import os
os.environ["KERAS_BACKEND"] = "torch" # or "jax" / "tensorflow"
from PIL import Image
import numpy as np
from kerasformers.models.inception_next import InceptionNextImageClassify, InceptionNextModel
model = InceptionNextImageClassify.from_weights("kerasformers/inception_next_base_sail_in1k")
backbone = InceptionNextModel.from_weights(
"kerasformers/inception_next_base_sail_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 InceptionNeXt variant the same way with
from_weights("kerasformers/<variant>")
:
| Variant | Hub |
|---|---|
inception_next_atto_sail_in1k
|
kerasformers/inception_next_atto_sail_in1k
|
inception_next_base_sail_in1k
|
kerasformers/inception_next_base_sail_in1k
|
inception_next_base_sail_in1k_384
|
kerasformers/inception_next_base_sail_in1k_384
|
inception_next_small_sail_in1k
|
kerasformers/inception_next_small_sail_in1k
|
inception_next_tiny_sail_in1k
|
kerasformers/inception_next_tiny_sail_in1k
|
Tips
-
Set
KERAS_BACKENDbefore importing Keras / kerasformers. -
InceptionNextImageClassifyreturns class logits;InceptionNextModelreturns features (as_backbone=Truefor multi-scale stages). - See docs and Loading Weights .
-
Upstream / timm checkpoints:
InceptionNextImageClassify.from_weights("hf:timm/inception_next_base.sail_in1k").
Special Thanks
A huge thank you to the InceptionNeXt authors and the timm / Hub communities for creating and releasing these models.
License: see YAML
license
(usually matches the upstream checkpoint).
Runs of zeromodels inception_next_base_sail_in1k on huggingface.co
45
Total runs
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3-day runs
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30-day runs
More Information About inception_next_base_sail_in1k huggingface.co Model
Url of inception_next_base_sail_in1k
inception_next_base_sail_in1k huggingface.co Url
Provider of inception_next_base_sail_in1k huggingface.co
Other API from zeromodels
Updated:August 27 2026
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