Instructions to use RevHard69MFJ/TRAILLOFPOSSIBILITIES with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use RevHard69MFJ/TRAILLOFPOSSIBILITIES with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("undefined") model.load_adapter("RevHard69MFJ/TRAILLOFPOSSIBILITIES", set_active=True) - Notebooks
- Google Colab
- Kaggle
metadata
license: apache-2.0
datasets:
- nvidia/PhysicalAI-Autonomous-Vehicles
language:
- en
metrics:
- accuracy
base_model:
- Qwen/Qwen3-VL-8B-Instruct
new_version: moonshotai/Kimi-K2-Thinking
library_name: adapter-transformers
tags:
- climate
- chemistry
- biology
- legal
- code
- medical
- agent