| | import torch |
| | from datasets import load_dataset |
| | from transformers import AutoImageProcessor, AutoModelForImageClassification |
| |
|
| | |
| | dataset = load_dataset("huggingface/cats-image") |
| | image = dataset["test"]["image"][0] |
| |
|
| | |
| | model_name = "Hyunil/CSATv2" |
| |
|
| | |
| | processor = AutoImageProcessor.from_pretrained(model_name, trust_remote_code=True) |
| | model = AutoModelForImageClassification.from_pretrained(model_name, trust_remote_code=True) |
| |
|
| | |
| | inputs = processor(image, return_tensors="pt") |
| |
|
| | |
| | with torch.no_grad(): |
| | logits = model(**inputs).logits |
| |
|
| | pred = logits.argmax(-1).item() |
| | print("Predicted label:", model.config.id2label[pred]) |