Instructions to use AyaF/ASL-Vit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AyaF/ASL-Vit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="AyaF/ASL-Vit") 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("AyaF/ASL-Vit") model = AutoModelForImageClassification.from_pretrained("AyaF/ASL-Vit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy
- Precision
- Recall
- F1Score
model-index:
- name: ArSL VIT
results:
- task:
name: Image Classification
type: image-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.9934656620025635
- name: Precision
type: Precision
value: 0.9939382672309875
- name: Recall
type: Recall
value: 0.9934656620025635
- name: F1Score
type: F1Score
value: 0.9933341145515442