Zero-Shot Classification
PEFT
Safetensors
English
lev
system-one
decision-model
calibrated-decisions
classification
routing
moderation
lora
Instructions to use interfaze-ai/lev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use interfaze-ai/lev with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-4B") model = PeftModel.from_pretrained(base_model, "interfaze-ai/lev") - Notebooks
- Google Colab
- Kaggle
| { | |
| "temperatures": { | |
| "choice:B:large": 0.6333014152276044, | |
| "choice:B": 0.6333014152276044, | |
| "noul:A": 2.3332930831706458, | |
| "score:A": 2.8033236630327885, | |
| "choice:A": 1.7666659539679779, | |
| "choice:A:small": 1.789783450971802, | |
| "choice:A:mid": 1.6085685001661532, | |
| "choice:A:large": 1.6641112617330986 | |
| }, | |
| "fitted_on": "calibration (transfer-selected)", | |
| "n_samples": { | |
| "choice:B:large": 10227, | |
| "choice:B": 10227, | |
| "noul:A": 12073, | |
| "score:A": 12258, | |
| "choice:A": 14133, | |
| "choice:A:small": 11480, | |
| "choice:A:mid": 1138, | |
| "choice:A:large": 1515 | |
| } | |
| } |