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hermes-research-agent

hermes-research-agent에는 ar0cket1에서 수집한 skills 7개가 있으며, 저장소 수준 직업 범위와 사이트 내 skill 상세 페이지를 제공합니다.

수집된 skills
7
Stars
28
업데이트
2026-03-10
Forks
1
직업 범위
직업 카테고리 2개 · 100% 분류됨
저장소 탐색

이 저장소의 skills

tinker
데이터 과학자

Run LLM post-training on Tinker with CPU-side orchestration and remote GPU execution. Use when preparing or launching SFT, DPO, or PPO-style runs, checkpointing, sampling checkpoints, or resuming long-running jobs through Hermes Research Agent.

2026-03-10
autonomous-llm-research
데이터 과학자

Run durable end-to-end LLM post-training research loops from zero-spec ideas to finished reports. Use when the goal is autonomous literature review, hypothesis selection, experiment planning, Tinker training, evaluation, checkpointing, and resumable long-running research work.

2026-03-10
eval-and-ablation
데이터 과학자

Plan and interpret model evaluations and ablations for post-training research. Use when comparing checkpoints, designing ablations, selecting benchmarks, or summarizing what changed after training.

2026-03-10
literature-to-experiment
데이터 과학자

Convert literature findings into concrete LLM experiment plans. Use when the agent has papers, blog posts, or benchmark notes and needs to turn them into hypotheses, training plans, dataset choices, and evaluation criteria.

2026-03-10
research-idea-generation
데이터 과학자

Generate and score candidate LLM research ideas from sparse user goals. Use when a project starts with no concrete benchmark, dataset, or training recipe and the agent needs to propose plausible, testable directions.

2026-03-10
research-reporting
사회 과학 연구 보조원

Produce clear iteration memos and final research summaries from project artifacts. Use when converting experiment state, training outcomes, evaluation results, and open questions into reports for later review.

2026-03-10
axolotl
데이터 과학자

Expert guidance for fine-tuning LLMs with Axolotl - YAML configs, 100+ models, LoRA/QLoRA, DPO/KTO/ORPO/GRPO, multimodal support

2026-03-09