SimpleTool-VLM-W4A16

SimpleTool-VLM

SimpleTool-VLM is a research release of a Qwen3-VL-4B model adapted for structured tool calls from images and text. It emits a function name and only the argument heads required by the supplied tool schema. The public release contains inference code and reproducibility notes; model weights are hosted separately on Hugging Face.

Highlights

• Direct and Adaptive modes.
• Function plus dynamically sized arg1...argN heads (N is the maximum property count in the supplied tools).
• Image input is passed as pixels; invoice values are not copied into hidden prompt fields.
• Raw branch outputs and legality are preserved for auditing.

Intended use

Research on real-time multimodal structured decisions, tool calling, and embodied-agent interfaces. This is not an OCR benchmark or a general invoice accounting system. Validate every action before execution.

Model variants

• BF16 merged checkpoint: Cialtion/SimpleTool-VLM.
• W4A16 checkpoint: Cialtion/SimpleTool-VLM-W4A16 (when the upload is complete).
• FP8 checkpoint: Cialtion/SimpleTool-VLM-FP8 (when the upload is complete).

The quantized variants use the same task adapter and tokenizer contract; backend support depends on the serving stack.

Quick start

The lightweight HTTP implementation is in inference/. It accepts one PNG, text messages, and OpenAI-style function tools. See examples/invoice_request.json. The service returns prediction.raw, prediction.legal, events, and server timings.

Limitations

This release does not claim strict adapter-to-merged numerical parity, arbitrary-image robustness, OCR superiority, or native Qwen chain-of-thought. Adaptive content is a short task-controlled field. The included invoice demo is an end-to-end protocol demonstration, not a financial approval system.

License and attribution

Code and release documentation are Apache-2.0. The checkpoint remains subject to the Qwen3-VL base-model license and any upstream terms. Users must review upstream terms before redistribution or commercial deployment.