Axion1-0/Axion-1.0-35B · 허깅페이스
Axion1-0/Axion-1.0-35B · Hugging Face
핵심 요약
데이터셋과 학습 레시피까지 모두 공개된 오픈 에이전트 모델 Axion 1.0이 공개되었습니다.
- 오픈 소스 모델 — 모델 가중치뿐만 아니라 데이터 구축, 학습 코드, 프롬프트까지 전체 과정을 공개함
- 간소화된 학습 — DPO나 복잡한 기법 없이 3단계의 효율적인 학습 과정만으로 강력한 에이전트 성능을 구현함
- 에이전트 성능 — 복잡한 추론과 외부 도구 활용 능력을 갖추어 상용 모델과 경쟁 가능한 수준을 보여줌
- 커뮤니티 반응 — 모델의 투명성과 공개 정신을 높게 평가하는 한편, 벤치마크 대상 선정에 대한 비판도 존재함
huggingface.co
원문 사이트로 이동
We introduce Axion 1.0, a fully open agent foundation model that combines strong and broad agentic capabilities with a remarkably simple training recipe. Axion 1.0 is trained in only three stages: two lightweight supervised fine-tuning stages followed by reinforcement learning, without dedicated mid-training, direct preference optimization (DPO), or on-policy distillation (OPD). The first SFT stage develops strong self-contained reasoning through model-aware data construction, where we synthesize challenging problems and adversarially strengthen them based on the base model's own successful solution strategies. The second stage extends these capabilities to tool-dependent reasoning through a scalable pipeline for constructing diverse and automatically verifiable tasks grounded in real-world data sources and deterministic computation. Finally, reinforcement learning further strengthens long-horizon reasoning and interaction with external tools and environments. Despite this compact training recipe, Axion 1.0 achieves strong performance across a broad suite of agentic benchmarks and is competitive with leading commercial models on several of them. Equally importantly, Axion 1.0 is open beyond model weights: we release the complete recipe, including data construction, generation, filtering, verification, prompts, and training code, enabling the entire development process to be reproduced and extended. Axion 1.0 demonstrates that strong agent foundation models can be both open and simple, offering a practical and reproducible path toward advancing open agentic intelligence.
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arXiv : https://arxiv.org/abs/2611.03233
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Dataset :
