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
File size: 880 Bytes
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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.
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