Create README.md

README.md

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+---
+pipeline_tag: text-generation
+inference: false
+license: apache-2.0
+library_name: transformers
+tags:
+- language
+- aquif_moe
+- text-generation-inference
+- 17b
+- qwen-like
+- bailing-like
+- science
+- math
+- code
+base_model:
+- inclusionAI/Ling-lite-base
+language:
+- en
+---
+
+# aquif-3-moe (17B) Thinking
+
+A high-performance mixture-of-experts language model optimized for efficiency, coding, science, and general use. With 17B total parameters and 2.8B active parameters, aquif-3-moe delivers competitive performance across multiple domains while maintaining computational efficiency.
+
+## Model Details
+
+**Architecture**: Mixture of Experts (MoE)  
+**Total Parameters**: 17 billion  
+**Active Parameters**: 2.8 billion  
+**License**: Apache 2.0  
+**Library**: transformers
+
+## Performance Benchmarks
+
+<img 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" width="1024px" alt="Benchmark Comparison Chart">
+
+| Metric                 | aquif-3-moe (Thinking 17B a2.8B) | Phi-4 (Thinking 14B) | Qwen3 (Thinking 8B) | DeepSeek R1 (Qwen3 8B) | Magistral Small (24B) | Gemini 2.5 Flash-Lite (Propr.) |
+| ---------------------- | -------------------------------- | -------------------- | ------------------- | ---------------------- | --------------------- | ------------------------------ |
+| LiveCodeBench (Coding) | **63.2**                         | *53.8*               | 58.1                | 60.5                   | 51.4                  | 59.3                           |
+| AIME 2024 (Math)       | **80.2**                         | *75.3*               | 74.7                | 65.0                   | 71.3                  | 70.3                           |
+| GPQA Diamond (Science) | *64.2*                           | **65.8**             | 62.0                | 61.1                   | 64.1                  | 62.5                           |
+| **Average**            | **69.2**                         | *65.0*               | 64.9                | 62.2                   | 62.3                  | 64.0                           |
+
+
+## Key Strengths
+
+- **Mathematical Reasoning**: Achieves 91.4% on MATH-500, demonstrating exceptional mathematical problem-solving capabilities
+- **Scientific Understanding**: Leads in GPQA Diamond with 56.7%, showing strong scientific reasoning
+- **Efficiency**: Delivers competitive performance with only 2.8B active parameters
+- **General Knowledge**: Strong MMLU performance at 83.2%
+
+## Usage
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+model_name = "aquiffoo/aquif-3-moe-17b-a2.8b-thinking"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Generate text
+inputs = tokenizer("Explain quantum entanglement:", return_tensors="pt")
+outputs = model.generate(**inputs, max_length=200)
+response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+```
+
+## Intended Use Cases
+
+- Mathematical problem solving and reasoning
+- Scientific research and analysis
+- Code generation and programming assistance
+- General question answering and text generation
+- Educational content creation
+
+## Model Architecture
+
+The mixture-of-experts architecture enables efficient scaling by activating only a subset of parameters for each input, providing the benefits of a larger model while maintaining computational efficiency comparable to much smaller dense models.
+
+## License
+
+Apache 2.0