MadhuryaPasan/Qwen3-ExpertTools

qwen3-1.7_expert_tools_v2_gguf : GGUF

This model was finetuned and converted to GGUF format using Unsloth.

Example usage:

• For text only LLMs: llama-cli -hf MadhuryaPasan/qwen3-1.7_expert_tools_v2_gguf --jinja
• For multimodal models: llama-mtmd-cli -hf MadhuryaPasan/qwen3-1.7_expert_tools_v2_gguf --jinja

Available Model files:

• qwen3-1.7b.F16.gguf
• qwen3-1.7b.Q8_0.gguf
• qwen3-1.7b.Q4_K_M.gguf

Evaluation Results

This model was evaluated using the BFCL (Berkeley Function Calling Leaderboard) evaluation framework to benchmark its tool-calling accuracy.

(Note: Evaluated on the 4-bit quantized (q4_K_M) versions. Full f16 precision may yield slightly higher results).

Evaluation Metric	Base Model (Qwen3 1.7B)	Fine-Tuned (ExpertTools)
Non-Live Overall Acc	29.73%	32.27%
AST Summary	29.73%	32.27%
Simple AST (Overall)	26.92%	33.08%
Python Simple AST	46.75%	52.25%
JavaScript Simple AST	34.00%	46.00%
Java Simple AST	0.00%	1.00%
Multiple AST	32.00%	35.50%
Parallel AST	44.00%	45.50%
Parallel Multiple AST	16.00%	15.00%
Irrelevance Detection	74.58%	61.25%

Ollama

An Ollama Modelfile is included for easy deployment. This was trained 2x faster with Unsloth