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const model = tf.sequential();
await pipeline('sentiment-analysis');
optimizer = torch.optim.Adam(lr=3e-4)
embeddings = model.encode(documents)
loss.backward()
predictions = model.predict(X_test)
tokenizer.encode(text, return_tensors='pt')
nn.TransformerEncoder(layer, 6)
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