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alt.freeweights.vision / vit-base-violence-detection
From: jaranohaal <huggingface.co/jaranohaal>Newsgroups: alt.freeweights.visionSubject:

vit-base-violence-detection

Date: 2026-11-15Commit: 3193109Signed: 2DC28CC7B26A283B ✓

Image classification model with 86M parameters. Safetensors weights, 686 MB in all. Published by jaranohaal under Apache-2.0.

86M params686MBvit-base-violence-detectionsafetensorspermissive
FactsParams86MSize686 MBFormatssafetensorsTaskimage classificationLicenseApache-2.0From sourcepermissive
$ fw get jaranohaal/vit-base-violence-detection
# manifest sha256 b015e5f5ab10… · 686 MB · 6 files
$ fw verify ./vit-base-violence-detection jaranohaal/vit-base-violence-detection
From sourceHosted (signed)jaranohaal/vit-base-violence-detectionLast check: 2026-11-15 03:37 UTC
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Ranked by fit to this model (safetensors), then by GitHub stars.

TransformersLocalAItinygradTriton Inference ServerBentoMLCTranslate2ExLlamaV2LitServe
OverviewModel cardFilesUse itLicenseProvenanceModel tree

Overview

Size
686 MB
Weights
343 MB (safetensors)
Parameters
86M
Formats
safetensors
Task
image classification
License
Apache-2.0 (permissive)
Files
6, each with a sha256
Publisher
jaranohaal
Added
2026-11-15
Section
alt.freeweights.vision
Lineage

Original release from the publisher.

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Publisher at the pinned commit→You

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BadgeHostLast checkResult
From sourcehuggingface.co2026-11-15 03:37 UTCpassed

Model card

From the publisher at commit 3193109. Shown as plain text with links; images open at the publisher.

ViT Base Violence Detection#

Model Description#

This is a Vision Transformer (ViT) model fine-tuned for violence detection. The model is based on google/vit-base-patch16-224-in21k and has been trained on the Real Life Violence Situations dataset from Kaggle to classify images into violent or non-violent categories.

Intended Use#

The model is intended for use in applications where detecting violent content in images is necessary. This can include:

  • Content moderation
  • Surveillance
  • Parental control software

Model accuracy#

Test accuracy for Vit Base = 98.80% Loss = 0.20038144290447235

How to Use#

Here is an example of how to use this model for image classification:

import torch
from transformers import ViTForImageClassification, ViTFeatureExtractor
from PIL import Image

# Load the model and feature extractor
model = ViTForImageClassification.from_pretrained('jaranohaal/vit-base-violence-detection')
feature_extractor = ViTFeatureExtractor.from_pretrained('jaranohaal/vit-base-violence-detection')

# Load an image
image = Image.open('image.jpg')

# Preprocess the image
inputs = feature_extractor(images=image, return_tensors="pt")

# Perform inference
with torch.no_grad():
    outputs = model(**inputs)
    logits = outputs.logits
    predicted_class_idx = logits.argmax(-1).item()

# Print the predicted class
print("Predicted class:", model.config.id2label[predicted_class_idx])

Files

6 files · 686 MBWeights 343 MB (safetensors). Sizes and sha256 from the signed manifest.
Hide all 6 files with their sha256
FileSizesha256
.gitattributes1.52 KB11ad7efa24975ee4b0c3c3a38ed18737f0658a5f75a0a96787b576a78a023361
README.md1.74 KBeec62e115b63cf716cdd6c6cda33580b6afe476f5e24a55185e754a832f87076
config.json523 B03652439b83bb9626e74675127b66e0278da16d74660e581a3be48663f75c626
model.safetensors343 MB9eec3237288742eb4267cb2cbbbdacba5bee889be4673215bfe40e1dbd5621a5
preprocessor_config.json580 B5e6895a8a80efa00a98656b6c24d202d7582614ceea87aa122f861120dc833c0
pytorch_model.bin343 MB8d5cb834bdca086c9bf1b071042f49c859675714f92800b55eebc936b37bd43e
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
31931091df pinned now2026-11-15 03:37 UTC6 files · 686 MB

Use it

$ fw get jaranohaal/vit-base-violence-detection
# manifest sha256 b015e5f5ab10… · 686 MB · 6 files
$ fw verify ./vit-base-violence-detection jaranohaal/vit-base-violence-detection
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/jaranohaal/vit-base-violence-detection.json --dir ./vit-base-violence-detection $ python3 fw.py verify ./vit-base-violence-detection ./jaranohaal__vit-base-violence-detection.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download jaranohaal/vit-base-violence-detection --revision 31931091dfd4ea08a30c42be0db8e1488263cbd5 --local-dir ./vit-base-violence-detection
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. 2026-11-15
Text in
README.md
Text sha256
eec62e115b63cf716cdd6c6cda33580b6afe476f5e24a55185e754a832f87076
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: jaranohaal <huggingface.co/jaranohaal>Newsgroups: alt.freeweights.visionSubject: vit-base-violence-detectionDate: 2026-11-15Commit: 3193109Signed: 2DC28CC7B26A283B ✓
Upstream
jaranohaal/vit-base-violence-detection
Pinned commit
31931091dfd4ea08a30c42be0db8e1488263cbd5
Manifest
vit-base-violence-detection.json · .minisig
Manifest sha256
b015e5f5ab106ec87c4a37e2cdd5013080867224143d9406171d28c2ccc8c929
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 03:37 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/jaranohaal/vit-base-violence-detection.json $ curl -O https://freeweights.allternit.com/manifests/jaranohaal/vit-base-violence-detection.json.minisig $ minisign -Vm vit-base-violence-detection.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

Model tree

1 model in the catalog name this one as their parent.

Quantizations
1
Quantizations 1
Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download jaranohaal/vit-base-violence-detection
Open in Freeweights Studio

Pull, verify and run it in the Allternit app on Desktop, web or phone.

Signed manifest
minisign, key 2DC28CC7B26A283B. vit-base-violence-detection.json. Provenance. Takedown history: none.
Source
huggingface.co/jaranohaal/vit-base-violence-detection

Variants

1 quantized or adapter build of vit-base-violence-detection. Each has its own license check and page.

SubjectSizeParamsLicenseDate
vit-base-violence-detection-ONNXHosted (signed) From: onnx-community in alt.freeweights.vision931 MB—Permissive2026-11-15

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