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dwightf/BerkshireGPT
BerkshireGPT is a text generation model from dwightf. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
BerkshireGPT is a 7 billion parameter model trained to be a value investor. It is trained on the Berkshire Hathaway annual shareholder meeting transcripts and other value investing material from the web.
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From the Hugging Face model README
BerkshireGPT is a 7 billion parameter model trained to be a value investor. It is trained on the Berkshire Hathaway annual shareholder meeting transcripts and other value investing material from the web.
It was fine-tuned from the FinGPT/fingpt-forecaster_dow30_llama2-7b_lora model.
It is good at giving advice on stocks as well as answering financial and stock questions.
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="dwightf/BerkshireGPT")
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("dwightf/BerkshireGPT")
model = AutoModelForCausalLM.from_pretrained("dwightf/BerkshireGPT")
More examples at the git repository here.
A unique input prompt was used to make sure the model focused on value investing
eval_prompt = f"""[INST]<<SYS>>\n You are a value investor giving your advice on stocks. And choosing whether to buy, sell, or hold them.
<</SYS>>
Q -{question}
[/INST]
"""
We are working on benchmarking the model on common financial benchmarks. We also plan on fine-tuning it on more data, speficially financial data.