1.3 KiB
1.3 KiB
license, base_model, tags, library_name, pipeline_tag
| license | base_model | tags | library_name | pipeline_tag | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| apache-2.0 | Qwen/Qwen3-1.7B-Instruct |
|
transformers | 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
Actioncalls forweb_searchandcalculator. - 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
pip install transformers torch accelerate bitsandbytes