---
license: apache-2.0
base_model: Qwen/Qwen3-1.7B-Instruct
tags:
- agentic
- reasoning
- tool-use
- safetensors
- unsloth
- cpu-optimized
library_name: transformers
pipeline_tag: text-generation
---

# 🤖 Agentic AI Suite (Qwen3-1.7B-Reasoning)

This model is a **Small Reasoning Model (SRM)** fine-tuned specifically for the "Goldilocks Zone" of AI deployment: **Powerful enough** to handle PhD-level research tasks and **fast enough** to run on a standard Hugging Face Free Tier CPU.

By utilizing the **Qwen3-1.7B** architecture, this model achieves high-logic reasoning while maintaining a tiny memory footprint (~1.1GB in 4-bit).

## 🌟 Features
- **Native Tool Calling**: Trained to output structured `Action` calls for `web_search` and `calculator`.
- **ReAct Framework**: Uses a "Thought -> Action -> Observation -> Final Answer" loop.
- **Safetensors Format**: Merged 4-bit weights for instant loading and high-speed CPU inference via `transformers`.
- **Zero-Latency Logic**: Optimized to respond in under 10 seconds on a 2-vCPU environment.

---

## 🛠️ How to Use (Agentic Implementation)

To use this model as a true agent, your code should intercept the `Action:` text and execute the corresponding Python function.

### 1. Requirements
```bash
pip install transformers torch accelerate bitsandbytes