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alt.freeweights.vision / convnext-small-224
From: facebook <huggingface.co/facebook>Newsgroups: alt.freeweights.visionSubject:

convnext-small-224

Date: 2026-11-14Commit: e0df91dSigned: 2DC28CC7B26A283B ✓

Image classification model with 50M parameters. Safetensors weights, 603 MB in all. Published by facebook under Apache-2.0.

50M params603MBconvnext-small-224safetensorspermissive
FactsParams50MSize603 MBFormatssafetensorsTaskimage classificationLicenseApache-2.0From sourcepermissive
$ fw get facebook/convnext-small-224
# manifest sha256 23b857f4781b… · 603 MB · 7 files
$ fw verify ./convnext-small-224 facebook/convnext-small-224
From sourceHosted (signed)facebook/convnext-small-224Last check: 2026-11-14 21:35 UTC
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Overview

Size
603 MB
Weights
201 MB (safetensors)
Parameters
50M
Formats
safetensors
Task
image classification
License
Apache-2.0 (permissive)
Files
7, each with a sha256
Publisher
facebook
Added
2026-11-14
Section
alt.freeweights.vision
Lineage

Original release from the publisher.

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From sourcehuggingface.co2026-11-14 21:35 UTCpassed

Model card

From the publisher at commit e0df91d. Shown as plain text with links; images open at the publisher.

ConvNeXT (large-sized model)#

ConvNeXT model trained on ImageNet-1k at resolution 224x224. It was introduced in the paper A ConvNet for the 2020s by Liu et al. and first released in this repository.

Disclaimer: The team releasing ConvNeXT did not write a model card for this model so this model card has been written by the Hugging Face team.

Model description#

ConvNeXT is a pure convolutional model (ConvNet), inspired by the design of Vision Transformers, that claims to outperform them. The authors started from a ResNet and "modernized" its design by taking the Swin Transformer as inspiration.

Image: model image

Intended uses & limitations#

You can use the raw model for image classification. See the model hub to look for fine-tuned versions on a task that interests you.

How to use#

Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes:

from transformers import ConvNextImageProcessor, ConvNextForImageClassification
import torch
from datasets import load_dataset

dataset = load_dataset("huggingface/cats-image")
image = dataset["test"]["image"][0]

processor = ConvNextImageProcessor.from_pretrained("facebook/convnext-small-224")
model = ConvNextForImageClassification.from_pretrained("facebook/convnext-small-224")

inputs = processor(image, return_tensors="pt")

with torch.no_grad():
    logits = model(**inputs).logits

# model predicts one of the 1000 ImageNet classes
predicted_label = logits.argmax(-1).item()
print(model.config.id2label[predicted_label]),

For more code examples, we refer to the documentation.

BibTeX entry and citation info#
@article{DBLP:journals/corr/abs-2201-03545,
  author    = {Zhuang Liu and
               Hanzi Mao and
               Chao{-}Yuan Wu and
               Christoph Feichtenhofer and
               Trevor Darrell and
               Saining Xie},
  title     = {A ConvNet for the 2020s},
  journal   = {CoRR},
  volume    = {abs/2201.03545},
  year      = {2022},
  url       = {https://arxiv.org/abs/2201.03545},
  eprinttype = {arXiv},
  eprint    = {2201.03545},
  timestamp = {Thu, 20 Jan 2022 14:21:35 +0100},
  biburl    = {https://dblp.org/rec/journals/corr/abs-2201-03545.bib},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}

Files

7 files · 603 MBWeights 201 MB (safetensors). Sizes and sha256 from the signed manifest.
Hide all 7 files with their sha256
FileSizesha256
.gitattributes1.23 KB98ccb431c012ebfe976280fbd45aea4cec7409935868ccecf3954370f96732a1
README.md3.06 KB210be2f23286a3cfd5f6996926c0ce2be2d9c96028615d0e29b12357180732b3
config.json69.6 KB1d26d7329549b7bd6c204a48282f937aeca9b0c79f28ddd6253884dd12c1cb09
model.safetensors201 MBd48dc1638cb83dba6ac8153d76491bbccc9485cf54890b1314eb687444714747
preprocessor_config.json266 Bfd575b890da5a949493e1d1e7a70bfcb9e4b99fe444004d2dbfa253add254741
pytorch_model.bin201 MBb3cbe154c1cb96aeff1fe8d0d4bd9808423ce941a9f70dac0ffe77f31abf9b83
tf_model.h5201 MB2d6654ccb434821d09842dbe1e0ce766231d31d92c011631440d470aeb7d16f4
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
e0df91dcc7 pinned now manifest updated, same commit2026-11-14 21:35 UTC7 files · 603 MB
e0df91dcc72026-11-14 21:35 UTC7 files · 603 MB

Use it

$ fw get facebook/convnext-small-224
# manifest sha256 23b857f4781b… · 603 MB · 7 files
$ fw verify ./convnext-small-224 facebook/convnext-small-224
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/facebook/convnext-small-224.json --dir ./convnext-small-224 $ python3 fw.py verify ./convnext-small-224 ./facebook__convnext-small-224.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download facebook/convnext-small-224 --revision e0df91dcc78dbc0f56be8fbecff706128aee7c28 --local-dir ./convnext-small-224
Run at home

License

Name
Apache License 2.0
Id
Apache-2.0
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
License as declared by the publisher. No person read it. 2026-11-14
Text in
README.md
Text sha256
210be2f23286a3cfd5f6996926c0ce2be2d9c96028615d0e29b12357180732b3
Terms gate
No extra terms beyond the license.

Read the license text

Licenses are checked against the license table. A custom license passes only after a person reads it.

Provenance

From: facebook <huggingface.co/facebook>Newsgroups: alt.freeweights.visionSubject: convnext-small-224Date: 2026-11-14Commit: e0df91dSigned: 2DC28CC7B26A283B ✓
Upstream
facebook/convnext-small-224
Pinned commit
e0df91dcc78dbc0f56be8fbecff706128aee7c28
Manifest
convnext-small-224.json · .minisig
Manifest sha256
23b857f4781b3da8225074c2f76d28e832bf10d91dd0ec5601d6a97fed12cd42
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-14 21:35 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/facebook/convnext-small-224.json $ curl -O https://freeweights.allternit.com/manifests/facebook/convnext-small-224.json.minisig $ minisign -Vm convnext-small-224.json -P RWQ7KGqyx4zCLXtUFOqvfv8L3g+8fpKJ1FsuxPyOYMF+4KufbUxKq1Oq $ shasum -a 256 <file> # compare with the Files tab

A manifest whose signature fails must be rejected. A file whose size or sha256 does not match must be discarded. Verify a download

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$ HF_ENDPOINT=https://freeweights.allternit.com hf download facebook/convnext-small-224
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Signed manifest
minisign, key 2DC28CC7B26A283B. convnext-small-224.json. Provenance. Takedown history: none.
Source
huggingface.co/facebook/convnext-small-224

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