Create README.md

README.md

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+![image/png](https://cdn-uploads.huggingface.co/production/uploads/63466107f7bd6326925fc770/b6xfld0bUDDAQIFvMCapD.png)
+
+# II-Search-4B
+
+
+<aside>
+
+A 4B parameter language model specialized in information seeking, multi-hop reasoning, and web-integrated search, achieving state-of-the-art performance among models of similar size.
+
+</aside>
+
+## Model Description
+
+II-Search-4B is a 4B parameter language model based on Qwen3-4B, fine-tuned specifically for information seeking tasks and web-integrated reasoning. It excels at complex multi-hop information retrieval, fact verification, and comprehensive report generation.
+
+### Key Features
+
+- Enhanced tool usage for web search and webpage visits
+- Multi-hop reasoning capabilities with sophisticated planning
+- Verified information retrieval with cross-checking
+- Strong performance on factual QA benchmarks
+- Comprehensive report generation for research queries
+
+## Training Methodology
+
+Our training process consisted of three key phases:
+
+### Phase 1: Tool Call Ability Stimulation
+
+We used a distillation approach from larger models (Qwen3-235B) to generate reasoning paths with function calling on multi-hop datasets. This established the base capabilities for tool use.
+
+### Phase 2: Reasoning Improvement
+
+We addressed initial limitations by:
+
+- Creating synthetic problems requiring more reasoning turns, inspired by Random Walk algorithm
+- Improving reasoning thought patterns for more efficient and cleaner reasoning paths
+
+### Phase 3: Rejection Sampling & Report Generation
+
+We applied:
+
+- Filtering to keep only high-quality reasoning traces (correct answers with proper reasoning)
+- STORM-inspired techniques to enhance comprehensive report generation
+
+## Performance
+
+| **Benchmark** | **Qwen3-4B** | **Jan-4B** | **WebSailor-3B** | **II-Search-4B** |
+| --- | --- | --- | --- | --- |
+| OpenAI/SimpleQA | 76.8 | 80.1 | 81.8 | 91.8 |
+| Google/Frames | 30.7 | 24.8 | 34.0 | 67.5 |
+| Seal_0 | 6.31 | 2.7 | 1.8 | 22.5 |
+
+### Tool Usage Comparison
+
+**Simple QA (SerpDev)**
+
+|  | **Qwen3-4B** | **Jan-4B** | **WebSailor-3B** | **II-Search-4B** |
+| --- | --- | --- | --- | --- |
+| # Search | 1.0 | 0.9 | 2.1 | 2.2 |
+| # Visit | 0.1 | 1.9 | 6.4 | 3.5 |
+| # Total Tools | 1.1 | 2.8 | 8.5 | 5.7 |
+
+All benchmark traces from models can be found at: https://huggingface.co/datasets/II-Vietnam/Inspect-Search-Models-Benchmarking-Result
+
+## Intended Use
+
+II-Search-4B is designed for:
+
+- Information seeking and factual question answering
+- Research assistance and comprehensive report generation
+- Fact verification and evidence-based reasoning
+- Educational and research applications requiring factual accuracy
+
+## Usage
+
+- LMStudio
+
+### Recommended Generation Parameters
+
+```python
+generate_cfg = {
+    'thought_in_content': True,
+    'top_p': 0.95,
+    'temperature': 0.6,
+    'repetition_penalty': 1.1,
+    'max_tokens': 2048
+}
+
+```
+
+- For a query that you need to find a short and accurate answer. Add the following phrase: "\n\nPlease reason step-by-step and put the final answer within \\boxed{}."
+
+## Citation
+
+```
+@misc{II-Search-4B,
+  author = {Intelligent Internet},
+  title = {II-Search-4B: Information Seeking and Web-Integrated Reasoning LLM},
+  year = {2025},
+  publisher = {Hugging Face},
+  journal = {Hugging Face Hub},
+  howpublished = {\url{https://huggingface.co/II-Vietnam/II-Search-4B}},
+}
+
+```