Image Classification
Transformers
TensorBoard
Safetensors
PyTorch
vit
huggingpics
Eval Results (legacy)
Instructions to use lokeshk/Face-Recognition-NM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lokeshk/Face-Recognition-NM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="lokeshk/Face-Recognition-NM") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("lokeshk/Face-Recognition-NM") model = AutoModelForImageClassification.from_pretrained("lokeshk/Face-Recognition-NM") - Notebooks
- Google Colab
- Kaggle
Face-Recognition-NM
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
Lokesh
Narendra_Modi
- Downloads last month
- 3
Model tree for lokeshk/Face-Recognition-NM
Evaluation results
- Accuracyself-reported1.000

