Model Details
Full Model IDdima806/facial_emotions_image_detection
Pipeline / Taskimage-classification
Librarytransformers
Downloads (all-time)606.6K
Likes120
Last Modified10/19/2024
Author / Orgdima806
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="dima806/facial_emotions_image_detection")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerspytorchsafetensorsvitimage-classificationbase_model:google/vit-base-patch16-224-in21kbase_model:finetune:google/vit-base-patch16-224-in21klicense:apache-2.0endpoints_compatibleregion: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
⬇ Downloads606.6K
❤️ Community Likes120
🛠️ 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.