Reinforcement Learning
PEFT
Safetensors
Korean
decision-making
connect-tycoon
connect-ai-lab
connectailab
lora
qwen3.5
Instructions to use hiro-coevolution/connectailab-rl-coevolution-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hiro-coevolution/connectailab-rl-coevolution-v1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-0.8B") model = PeftModel.from_pretrained(base_model, "hiro-coevolution/connectailab-rl-coevolution-v1") - Notebooks
- Google Colab
- Kaggle
Download connectailab.json from hiro-coevolution/connectailab-rl-coevolution-v1: direct link, hf CLI and curl.
- Browser
- Download file 1.2 kB
-
https://huggingface.co/hiro-coevolution/connectailab-rl-coevolution-v1/resolve/main/connectailab.json
- Command line
-
hf download hf://hiro-coevolution/connectailab-rl-coevolution-v1/connectailab.json
-
curl -L -o connectailab.json https://huggingface.co/hiro-coevolution/connectailab-rl-coevolution-v1/resolve/main/connectailab.json
1.2 kB
| { | |
| "format": "connectailab/1", | |
| "repo": "hiro-coevolution/connectailab-rl-coevolution-v1", | |
| "base_model": "Qwen/Qwen3.5-0.8B", | |
| "backend": "torch", | |
| "adapter": ".", | |
| "author": null, | |
| "values": { | |
| "이익": 1.0, | |
| "고객 만족": 1.0, | |
| "위험": 1.0 | |
| }, | |
| "profile": "general", | |
| "results": { | |
| "Qwen 학습 전": { | |
| "accuracy": 0.2916666666666667, | |
| "regret": 2.3652392857142943, | |
| "n": 840 | |
| }, | |
| "지도학습": { | |
| "accuracy": 0.8428571428571429, | |
| "regret": 1.4737702380952404, | |
| "n": 840 | |
| }, | |
| "강화학습": { | |
| "accuracy": 0.8416666666666667, | |
| "regret": 1.4243166666666682, | |
| "n": 840, | |
| "profit": 892.2149999999999, | |
| "sat": 0.97705, | |
| "incidents": 12.0, | |
| "months": 2, | |
| "card": { | |
| "cases": 713, | |
| "fraud": 177, | |
| "caught": 147, | |
| "missed": 30, | |
| "false_block": 69, | |
| "human": 0, | |
| "loss": 2365.5099999999998, | |
| "fraud_loss": 1830.3999999999999, | |
| "block_loss": 535.1099999999999, | |
| "human_cost": 0.0, | |
| "allow_all_loss": 8618.1, | |
| "saved": 0.7255183857230713 | |
| } | |
| } | |
| } | |
| } |