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removed unnecessary imports (#367)
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@ -52,7 +52,6 @@ def get_model_and_tokenizer():
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model.out_head = torch.nn.Linear(in_features=GPT_CONFIG_124M["emb_dim"], out_features=num_classes)
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# Then load model weights
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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checkpoint = torch.load(model_path, map_location=device, weights_only=True)
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model.load_state_dict(checkpoint)
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model.to(device)
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@ -71,7 +70,6 @@ async def main(message: chainlit.Message):
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The main Chainlit function.
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"""
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user_input = message.content
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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label = classify_review(user_input, model, tokenizer, device, max_length=120)
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