# Load model directly
from transformers import AutoModelForImageClassification
model = AutoModelForImageClassification.from_pretrained("ozair23/autotrain-w5nk2-rvmqx", device_map="auto")Quick Links
Model Trained Using AutoTrain
- Problem type: Image Classification
Validation Metrics
No validation metrics available
#Inference Pipeline
-Here is how to use this model to classify an image of the COCO 2017 dataset into one of the 1,000 ImageNet classes:
from transformers import AutoModelForImageClassification, AutoProcessor
model = AutoModelForImageClassification.from_pretrained("ozair23/autotrain-w5nk2-rvmqx")
processor = AutoProcessor.from_pretrained("ozair23/autotrain-w5nk2-rvmqx")
def predict(image):
inputs = processor(images=image, return_tensors="pt")
outputs = model(**inputs)
return outputs
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Model tree for ozair23/autotrain-w5nk2-rvmqx
Base model
microsoft/resnet-50
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ozair23/autotrain-w5nk2-rvmqx") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")