metadata
license: apache-2.0
language:
- en
tags:
- reinforcement-learning
- teacher-student
- adaptive-learning
base_model: Qwen/Qwen3-8B
datasets:
- Arc-Intelligence/Arc-ATLAS-Teach-v0
ATLAS-8B-Thinking
Teacher model for adaptive RL training that improves any student model's performance through diagnostic probing and conditional teaching.
Performance
| Metric | Improvement |
|---|---|
| Average accuracy | +15.7% |
| Completion rate | +31% |
| Response efficiency | -50% tokens |
Quick Start
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
"Arc-Intelligence/ATLAS-8B-Thinking",
torch_dtype="auto",
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained("Arc-Intelligence/ATLAS-8B-Thinking")
Training Framework
Use with ATLAS framework:
git clone https://github.com/Arc-Intelligence/ATLAS
cd ATLAS
bash scripts/install_py312.sh
# Run training
scripts/launch.sh 4 configs/run/teacher_sft.yaml
scripts/launch_with_server.sh 1 3 configs/run/teacher_rcl.yaml
Model Details
- Base: Qwen3-8B
- Context: 8192 tokens
- Training: SFT → RL with GRPO
- Dataset: Arc-ATLAS-Teach-v0
Citation
@article{atlas2025,
title={ATLAS: Adaptive Training Methodology for RL},
author={Arc Intelligence},
year={2025}
}