Image Classification
Transformers
PyTorch
TensorFlow
Safetensors
resnet
image-feature-extraction
vision
Instructions to use grelade/mmx-feature-extraction with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use grelade/mmx-feature-extraction with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="grelade/mmx-feature-extraction") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("grelade/mmx-feature-extraction") model = AutoModel.from_pretrained("grelade/mmx-feature-extraction", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!