Instructions to use adimyth/compass-lora-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use adimyth/compass-lora-v2 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, "adimyth/compass-lora-v2") - Notebooks
- Google Colab
- Kaggle
File size: 1,003 Bytes
bfa8af0 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | {
"temperatures": {
"choice": 2.0,
"score": 2.0,
"noul": 2.25
},
"fitted_on": [
"dev/splits_v2/calibration-hard.jsonl"
],
"model": "compass-fusion-lora-qwen3.5-4b-compass-prompt-2",
"readout": "fusion",
"head": null,
"fusion_weight": 0.5,
"n_items": 178,
"report": {
"choice": {
"n": 45,
"fit_half_T": 0.25,
"shipped_T": 2.0,
"held_out_ece_before": 0.0937,
"held_out_ece_after": 0.0931,
"held_out_nll_before": 0.5269,
"held_out_nll_after": 1.2941
},
"score": {
"n": 90,
"fit_half_T": 2.25,
"shipped_T": 2.0,
"held_out_ece_before": 0.0286,
"held_out_ece_after": 0.0698,
"held_out_nll_before": 0.0993,
"held_out_nll_after": 0.1376
},
"noul": {
"n": 43,
"fit_half_T": 2.0,
"shipped_T": 2.25,
"held_out_ece_before": 0.1522,
"held_out_ece_after": 0.1151,
"held_out_nll_before": 0.5846,
"held_out_nll_after": 0.4233
}
}
} |