Instructions to use doraking/finpath-autoscientist-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use doraking/finpath-autoscientist-model with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("togethercomputer/gpt-oss-20b-bf16") model = PeftModel.from_pretrained(base_model, "doraking/finpath-autoscientist-model") - Notebooks
- Google Colab
- Kaggle
metadata
base_model: openai/gpt-oss-20b
library_name: peft
license: apache-2.0
language:
- en
tags:
- adaption
- autoscientist
- personal-finance
- lora
FinPath AutoScientist Model
LoRA adapter trained with Adaption AutoScientist for grounded personal-finance reasoning.
Base Model
openai/gpt-oss-20b
Data
- Source: https://huggingface.co/datasets/doraking/finpath-autoscientist-data
- Adapted: https://huggingface.co/datasets/doraking/finpath-autoscientist-adapted
Intended Behavior
Return the direct result, show the calculation, explain tradeoffs, provide practical next steps, and distinguish educational information from individualized financial advice.
Limitations
Validate calculations and applicable rules before real-world use. This model is not a financial adviser and does not account for every jurisdiction, product, or personal circumstance.