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README.md
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- Personalized financial reasoning
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### Model Description
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- **License:** MIT
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Use the code below to get started with the model.
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```python
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from huggingface_hub import login
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from transformers import AutoTokenizer, AutoModelForCausalLM
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from peft import PeftModel
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login(token="")
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tokenizer = AutoTokenizer.from_pretrained("unsloth/Qwen3-1.7B",)
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base_model = AutoModelForCausalLM.from_pretrained(
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"unsloth/Qwen3-1.7B",
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device_map={"": 0}
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)
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model = PeftModel.from_pretrained(base_model,"khazarai/Personal-Finance-R2")
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question =
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Hi!
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I was just accepted into the full-time software engineering program with Flatiron and have approx. $0 to my name.
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I know I can get a loan with either Climb or accent with around 6.50% interest, is this a good option?
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I would theoretically be paying near $600/month.
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I really enjoy coding and would love to start a career in tech but the potential $19k price tag is pretty scary. Any advice?
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"""
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messages = [
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### Training Data
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- Dataset Overview:
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It covers a wide range of subjects including budgeting, saving, investing, credit management, retirement planning, insurance, and financial literacy.
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- Data Format:
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- Personalized financial reasoning
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### Model Description
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- **License:** MIT
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Use the code below to get started with the model.
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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from peft import PeftModel
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tokenizer = AutoTokenizer.from_pretrained("unsloth/Qwen3-1.7B",)
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base_model = AutoModelForCausalLM.from_pretrained(
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"unsloth/Qwen3-1.7B",
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device_map={"": 0}
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)
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model = PeftModel.from_pretrained(base_model,"khazarai/Personal-Finance-R2")
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question = """ I just got accepted into Flatiron's full-time software engineering bootcamp, but I have basically no savings and the $19k price tag is freaking me out.
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I really love coding and want to break into tech, but I'm looking at taking out a loan through Climb or Ascent with around 6.5% interest—that'd mean paying like $600 a month after.
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Is this a smart move? I'm torn between chasing this opportunity and being terrified of the debt. Any advice?
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"""
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messages = [
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### Training Data
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- Dataset Overview:
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Kuvera-PersonalFinance-V2.1 is a collection of high-quality instruction-response pairs focused on personal finance topics.
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It covers a wide range of subjects including budgeting, saving, investing, credit management, retirement planning, insurance, and financial literacy.
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- Data Format:
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