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kerasformers/
poolformer_s24_sail_in1k

Name: poolformer_s24_sail_in1k
Rating: 2.5 (38 reviews)

timm/poolformer_s24.sail_in1k

finetune

apache-2.0

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Run PoolFormer with Keras 3: JAX, PyTorch, or TensorFlow

GitHub

kerasformers/poolformer_s24_sail_in1k

Paper: MetaFormer Is Actually What You Need for Vision (arXiv:2111.11418) · HF Papers

PoolFormer shows MetaFormer with pooling as the token mixer can match strong vision baselines. Classifier or 4-stage backbone.

For more details on the model, please go to the upstream model card.

Pure-Keras 3 conversion of timm/poolformer_s24.sail_in1k for kerasformers. One implementation runs unmodified on TensorFlow / Torch / JAX.

This is an image-classification / backbone checkpoint (PoolFormerImageClassify / PoolFormerModel).

✨ Quick start

python

import os
os.environ["KERAS_BACKEND"] = "torch"  # or "jax" / "tensorflow"

from PIL import Image
import numpy as np
from kerasformers.models.poolformer import PoolFormerImageClassify, PoolFormerModel

model = PoolFormerImageClassify.from_weights("kerasformers/poolformer_s24_sail_in1k")
backbone = PoolFormerModel.from_weights(
    "kerasformers/poolformer_s24_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 PoolFormer variant the same way with from_weights("kerasformers/<variant>"):

Variant	Hub
`poolformer_m36_sail_in1k`	`kerasformers/poolformer_m36_sail_in1k`
`poolformer_m48_sail_in1k`	`kerasformers/poolformer_m48_sail_in1k`
`poolformer_s12_sail_in1k`	`kerasformers/poolformer_s12_sail_in1k`
`poolformer_s24_sail_in1k`	`kerasformers/poolformer_s24_sail_in1k`
`poolformer_s36_sail_in1k`	`kerasformers/poolformer_s36_sail_in1k`

Tips

Set KERAS_BACKEND before importing Keras / kerasformers.
PoolFormerImageClassify returns class logits; PoolFormerModel returns features (as_backbone=True for multi-scale stages).
See docs and Loading Weights.
Upstream / timm checkpoints: PoolFormerImageClassify.from_weights("hf:timm/poolformer_s24.sail_in1k").

Special Thanks

A huge thank you to the PoolFormer authors and the timm / Hub communities for creating and releasing these models.

License: see YAML license (usually matches the upstream checkpoint).