Add model card

README.md

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+---
+license: apache-2.0
+language:
+- en
+- zh
+base_model: Qwen/Qwen2.5-32B-Instruct
+tags:
+- aiops
+- root-cause-analysis
+- openrca
+- tool-calling
+---
+
+# Netis N1
+
+Netis N1 is a 32B-parameter model specialized for **intelligent IT operations (AIOps)**, fine-tuned from Qwen2.5-32B-Instruct using Continual Pre-training, SFT, and RL.
+
+## Highlights
+
+- **OpenRCA Scoring 26.0%** — on par with Claude Opus 4.5 (26.9%), surpassing GPT Codex (21.0%) and DeepSeek (13.6%)
+- General capabilities preserved or improved (GPQA +9.6%, MMLU-Pro +3.3%, IFEval +1.0%)
+- Two-stage diagnostic workflow: tool-call planning + fault localization
+
+## Evaluation Results
+
+| Benchmark              | Base (Qwen2.5-32B) |          Netis N1 |
+| ---------------------- | -----------------: | ----------------: |
+| OpenRCA Bank (scoring) |                  — |         **26.0%** |
+| MMLU-Pro (300)         |              63.7% |         **67.0%** |
+| GPQA Diamond (198)     |              44.4% |         **54.0%** |
+| IFEval (100)           |      86.0% / 90.5% | **87.0% / 91.2%** |
+| GSM8K (1319)           |              91.5% |             91.4% |
+| AIME (90)              |              16.7% |             11.1% |
+| HLE (100)              |               2.0% |              1.0% |
+
+## How to Evaluate
+
+Serve with vLLM and run the eval suite:
+
+```bash
+# Start vLLM server
+python -m vllm.entrypoints.openai.api_server \
+  --model ./netis-n1 --port 6777 --max-model-len 20000
+
+# OpenRCA eval (requires OpenRCA Bank dataset)
+python eval_model.py --llm-backend vllm --vllm-base-url http://localhost:6777
+
+# General benchmarks (MMLU-Pro, GPQA, AIME, IFEval)
+python eval_multi_model.py --name netis-n1 --url http://localhost:6777 --model netis-n1
+```
+
+## License
+
+Apache 2.0