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Update app.py
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app.py
CHANGED
@@ -49,7 +49,7 @@ def check_existing_model(stock_symbol, start_date, end_date):
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state = repo_id in [model.modelId for model in hf_api.list_models()]
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return state
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-
@spaces.GPU(duration=
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def train_stock_model(stock_symbol, start_date, end_date, feature_range=(10, 100), data_seq_length=256, epochs=10, batch_size=16, learning_rate=2e-4):
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repo_id = f"Q-bert/StockLlama-tuned{stock_symbol}-{start_date}_{end_date}"
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@@ -124,7 +124,7 @@ def train_stock_model(stock_symbol, start_date, end_date, feature_range=(10, 100
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)
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return f"Training completed and model saved for {stock_symbol} from {start_date} to {end_date}."
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@spaces.GPU(duration=
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def gradio_train_stock_model(stock_symbol, start_date, end_date, feature_range_min, feature_range_max, data_seq_length, epochs, batch_size, learning_rate):
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feature_range = (feature_range_min, feature_range_max)
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result = train_stock_model(
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state = repo_id in [model.modelId for model in hf_api.list_models()]
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return state
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+
@spaces.GPU(duration=120)
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def train_stock_model(stock_symbol, start_date, end_date, feature_range=(10, 100), data_seq_length=256, epochs=10, batch_size=16, learning_rate=2e-4):
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repo_id = f"Q-bert/StockLlama-tuned{stock_symbol}-{start_date}_{end_date}"
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)
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return f"Training completed and model saved for {stock_symbol} from {start_date} to {end_date}."
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+
@spaces.GPU(duration=120)
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def gradio_train_stock_model(stock_symbol, start_date, end_date, feature_range_min, feature_range_max, data_seq_length, epochs, batch_size, learning_rate):
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feature_range = (feature_range_min, feature_range_max)
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result = train_stock_model(
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