Model Details
Full Model IDAdamCodd/vit-base-nsfw-detector
Pipeline / Taskimage-classification
Librarytransformers.js
Downloads (all-time)1.1M
Likes75
Last Modified12/3/2024
Author / OrgAdamCodd
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("image-classification", model="AdamCodd/vit-base-nsfw-detector")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformers.jsonnxsafetensorsvitimage-classificationtransformersnlpbase_model:google/vit-base-patch16-384base_model:quantized:google/vit-base-patch16-384license:apache-2.0model-indexdeploy:azureregion:us
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Access model files, inference API, and full documentation on Hugging Face.
Open on Hugging Face →Browse Model Files ↗← Browse All Models🖼️ Task: Image Classification
This model is designed for the Image Classification task. Explore more models for this use case.
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⬇ Downloads1.1M
❤️ Community Likes75
🛠️ Requirements
- →Install: pip install transformers.js
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.