sagar27kumar/ECG-XRAY-dataset
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How to use sagar27kumar/sagarsahu_ECG-XRAY-ViT with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="sagar27kumar/sagarsahu_ECG-XRAY-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("sagar27kumar/sagarsahu_ECG-XRAY-ViT")
model = AutoModelForImageClassification.from_pretrained("sagar27kumar/sagarsahu_ECG-XRAY-ViT")This model is a fine-tuned version of google/vit-large-patch32-384 on an unknown dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.2773 | 1.0 | 116 | 0.1050 |
| 0.0739 | 2.0 | 232 | 0.0919 |
Base model
google/vit-large-patch32-384