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app.py
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@@ -312,9 +312,12 @@ demo = gr.Interface(
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This model is finetuned on Llama2-7b-chat-hf with LoRA on the past year's DOW30 market data. Inference in this demo uses fp16 and **welcomes any ticker symbol**.
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Company profile & Market news & Basic financials & Stock prices are retrieved using **yfinance & finnhub**.
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This is just a demo showing what this model is capable of. Results inferred from randomly chosen news can be strongly biased.
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For more detailed and customized implementation, refer to our FinGPT project: <https://github.com/AI4Finance-Foundation/FinGPT>
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**Disclaimer: Nothing herein is financial advice, and NOT a recommendation to trade real money. Please use common sense and always first consult a professional before trading or investing.**
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"""
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This model is finetuned on Llama2-7b-chat-hf with LoRA on the past year's DOW30 market data. Inference in this demo uses fp16 and **welcomes any ticker symbol**.
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Company profile & Market news & Basic financials & Stock prices are retrieved using **yfinance & finnhub**.
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For more detailed and customized implementation, refer to our FinGPT project: <https://github.com/AI4Finance-Foundation/FinGPT>
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⚠️Warning: This is just a demo showing what this model is capable of. During each individual inference, company news is **randomly sampled** from all the news from designated weeks, which might result in **unstable predictions**.
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We suggest users deploy the [original model](https://huggingface.co/FinGPT/fingpt-forecaster_dow30_llama2-7b_lora) or clone this space and inference with more carefully selected news in their own favorable ways.
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Setting do_sample=False or modifying the temperature during the generation process also helps stabilize the prediction result.
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**Disclaimer: Nothing herein is financial advice, and NOT a recommendation to trade real money. Please use common sense and always first consult a professional before trading or investing.**
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"""
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)
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