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
| 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. | |