Instructions to use davanstrien/autotrain-encyclopedia_britannica with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/autotrain-encyclopedia_britannica with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="davanstrien/autotrain-encyclopedia_britannica") 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("davanstrien/autotrain-encyclopedia_britannica") model = AutoModelForImageClassification.from_pretrained("davanstrien/autotrain-encyclopedia_britannica", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Metadata Report Card
#1
by davanstrien - opened
Model metadata report card
This is an automatically produced metadata quality report card for davanstrien/autotrain-encyclopedia_britannica. This report is meant as a POC!
Breakdown of metadata fields for your model
| Metadata Field | Provided Value |
|---|---|
| tags | Field Missing |
| license | Field Missing |
| library_name | Field Missing |
| datasets | Field Missing |
| metrics | Field Missing |
| co2 | Field Missing |
| pipeline_tag | Field Missing |
You scored a metadata coverage grade of: 0.0%
We're not angry we're just disappointed! Model metadata is super important. Please try harder...