Edit model card

Usage

import torch
from informer_models import InformerConfig, InformerForSequenceClassification

model = InformerForSequenceClassification.from_pretrained("BrachioLab/supernova-classification")

model.to(device)
model.eval()
y_true = []
y_pred = []
for i, batch in enumerate(test_dataloader):
    print(f"processing batch {i}")
    batch = {k: v.to(device) for k, v in batch.items() if k != "objid"}
    with torch.no_grad():
        outputs = model(**batch)
    y_true.extend(batch['labels'].cpu().numpy())
    y_pred.extend(torch.argmax(outputs.logits, dim=2).squeeze().cpu().numpy())
print(f"accuracy: {sum([1 for i, j in zip(y_true, y_pred) if i == j]) / len(y_true)}")
Downloads last month
133
Inference API
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.