Text Classification
PEFT
Safetensors
English
agents
llm-agents
tool-use
function-calling
decision-making
decision-model
lora
qwen3
Instructions to use JevAgentHarness/AgentDecision-4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use JevAgentHarness/AgentDecision-4B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-4B") model = PeftModel.from_pretrained(base_model, "JevAgentHarness/AgentDecision-4B") - Notebooks
- Google Colab
- Kaggle
Download thresholds.json from JevAgentHarness/AgentDecision-4B: direct link, hf CLI and curl.
- Browser
- Download file 737 Bytes
-
https://huggingface.co/JevAgentHarness/AgentDecision-4B/resolve/main/thresholds.json
- Command line
-
hf download hf://JevAgentHarness/AgentDecision-4B/thresholds.json
-
curl -L -o thresholds.json https://huggingface.co/JevAgentHarness/AgentDecision-4B/resolve/main/thresholds.json
737 Bytes
| { | |
| "description": "Confidence thresholds of the cascade: the harness uses the model's answer when its calibrated confidence (calibration.json applied) is >= tau, and lets the agent LLM decide otherwise. Refit them for another agent LLM, other tools or another task family.", | |
| "rule": ">=", | |
| "agent_llm": "gemini-3.5-flash", | |
| "tool_select": 0.44503032941063925, | |
| "tool_params": 0.9958731532096863, | |
| "fitted_on": "the agent states of a shadow-mode calibration run (150 DecisionGym tasks, seeds 5000-5149, Gemini 3.5 Flash as the agent LLM), answered by this model with calibration.json applied", | |
| "source": "research/results/explore/e21b_shift_cascade/cal/fits.json; harness profile research/configs/harness/explore_e21b_e12_final.yaml" | |
| } | |