Transformers
English
triangulated-inference
edge-ai
ensemble
small-models
nova-triangle
gradient-ascent
self-correcting
Instructions to use Wayfinder6/nova-triangle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wayfinder6/nova-triangle with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Wayfinder6/nova-triangle", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| """ | |
| Nova Triangle — Three small models that correct each other. | |
| A triangulated inference framework. Instead of one large model guessing, | |
| three small models deliberate, disagree, and converge. The disagreement | |
| is the signal. | |
| Usage: | |
| from nova_triangle import Triangle | |
| tri = Triangle( | |
| models=["HuggingFaceTB/SmolLM2-360M", "Qwen/Qwen2.5-0.5B", "microsoft/phi-1_5"], | |
| ) | |
| result = tri.process("Translate this cuneiform tablet") | |
| print(result.answer) | |
| print(result.confidence) | |
| print(result.disagreement) | |
| """ | |
| from nova_triangle.triangle import Triangle | |
| from nova_triangle.result import TriangleResult | |
| __version__ = "0.1.0" | |
| __all__ = ["Triangle", "TriangleResult"] | |