Model Details
Full Model IDgoogle/vit-base-patch16-224
Pipeline / Taskimage-classification
Librarytransformers
Downloads (all-time)8.5M
Likes1.0K
Last Modified9/5/2023
Author / Orggoogle
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="google/vit-base-patch16-224")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchtfjaxsafetensorsvitimage-classificationvisiondataset:imagenet-1kdataset:imagenet-21karxiv:2010.11929arxiv:2006.03677license:apache-2.0endpoints_compatibledeploy: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.
All Image Classification Models →📊 Popularity
⬇ Downloads8.5M
❤️ Community Likes1.0K
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.