SequentialLearning
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SuperLinear

mixture-of-experts

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lirannoc commited on Sep 25

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cecd232

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1 Parent(s): 94a91a3

Update README.md

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@@ -48,8 +48,8 @@ input_data = torch.randn(1, 1, 512)
 # Generate predictions
 with torch.no_grad():
     outputs = model(inputs_embeds=input_data, pred_len=96, get_prob = True)
-    preds = output.logits # Predicted values
-    probs = output.attentions  # Expert probabilities stored here
 ```

 # Generate predictions
 with torch.no_grad():
     outputs = model(inputs_embeds=input_data, pred_len=96, get_prob = True)
+    preds = outputs.logits # Predicted values
+    probs = outputs.attentions  # Expert probabilities stored here
 ```