ToolGrad 4B
ToolGrad 4B is a fine-tuned version of google/gemma-3-4b-it optimized for function calling and tool-use tasks. It is trained on the dataset generated using the method described in our paper ToolGrad: Efficient Tool-use Dataset Generation with Textual "Gradients" (ACL 2026 Finding). The codebase is available at our GitHub Repository.
Model Details
- Developed by: Zhongyi Zhou
- Model Type: Causal Language Model
- Base Model: google/gemma-3-4b-it
- License: gemma-terms-of-use
Intended Use
Single-turn tool-use tasks.
Evaluation Results
Evaluated on the Berkeley Function Calling Leaderboard (BFCL) v1 & v2:
Overall & Hallucination Scores
<table style="border-collapse: collapse;">
<thead>
<tr>
<th rowspan="2" style="border-bottom: 1px solid #ddd; padding: 8px;">Model</th>
<th align="center" style="border-left: 1px solid #ddd; border-bottom: 1px solid #ddd; padding: 8px;">Non-live</th>
<th align="center" style="border-left: 1px solid #ddd; border-bottom: 1px solid #ddd; padding: 8px;">Live</th>
<th colspan="2" align="center" style="border-left: 1px solid #ddd; border-bottom: 1px solid #ddd; padding: 8px;">Halluc.</th>
</tr>
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<th align="center" style="border-left: 1px solid #ddd; border-bottom: 1px solid #ddd; padding: 8px;">Overall</th>
<th align="center" style="border-left: 1px solid #ddd; border-bottom: 1px solid #ddd; padding: 8px;">Overall</th>
<th align="center" style="border-left: 1px solid #ddd; border-bottom: 1px solid #ddd; padding: 8px;">Rel.</th>
<th align="center" style="border-bottom: 1px solid #ddd; padding: 8px;">Irrel.</th>
</tr>
</thead>
<tbody>
<tr>
<td style="padding: 8px;"><b>Gemma-3 4B</b></td>
<td align="center" style="border-left: 1px solid #ddd; padding: 8px;">61.12%</td>
<td align="center" style="border-left: 1px solid #ddd; padding: 8px;">60.84%</td>
<td align="center" style="border-left: 1px solid #ddd; padding: 8px;">53.94%</td>
<td align="center" style="padding: 8px;">100.00%</td>
</tr>
<tr>
<td style="padding: 8px;"><b>ToolGrad 4B</b></td>
<td align="center" style="border-left: 1px solid #ddd; padding: 8px;">72.46% ↑</td>
<td align="center" style="border-left: 1px solid #ddd; padding: 8px;">65.58% ↑</td>
<td align="center" style="border-left: 1px solid #ddd; padding: 8px;">93.75%</td>
<td align="center" style="padding: 8px;">59.27%</td>
</tr>
</tbody>
</table>
Detailed Category Scores
<table style="border-collapse: collapse;">
<thead>
<tr>
<th rowspan="2" style="border-bottom: 1px solid #ddd; padding: 8px;">Model</th>
<th colspan="4" align="center" style="border-left: 1px solid #ddd; border-bottom: 1px solid #ddd; padding: 8px;">Non-live</th>
<th colspan="4" align="center" style="border-left: 1px solid #ddd; border-bottom: 1px solid #ddd; padding: 8px;">Live</th>
</tr>
<tr>
<th align="center" style="border-left: 1px solid #ddd; border-bottom: 1px solid #ddd; padding: 8px;">Simple</th>
<th align="center" style="border-bottom: 1px solid #ddd; padding: 8px;">Multi</th>
<th align="center" style="border-bottom: 1px solid #ddd; padding: 8px;">Par</th>
<th align="center" style="border-bottom: 1px solid #ddd; padding: 8px;">MultiPar</th>
<th align="center" style="border-left: 1px solid #ddd; border-bottom: 1px solid #ddd; padding: 8px;">Simple</th>
<th align="center" style="border-bottom: 1px solid #ddd; padding: 8px;">Multi</th>
<th align="center" style="border-bottom: 1px solid #ddd; padding: 8px;">Par</th>
<th align="center" style="border-bottom: 1px solid #ddd; padding: 8px;">MultiPar</th>
</tr>
</thead>
<tbody>
<tr>
<td style="padding: 8px;"><b>Gemma-3 4B</b></td>
<td align="center" style="border-left: 1px solid #ddd; padding: 8px;">64.50%</td>
<td align="center" style="padding: 8px;">88.00%</td>
<td align="center" style="padding: 8px;">56.00%</td>
<td align="center" style="padding: 8px;">36.00%</td>
<td align="center" style="border-left: 1px solid #ddd; padding: 8px;">70.93%</td>
<td align="center" style="padding: 8px;">59.35%</td>
<td align="center" style="padding: 8px;">25.00%</td>
<td align="center" style="padding: 8px;">41.67%</td>
</tr>
<tr>
<td style="padding: 8px;"><b>ToolGrad 4B</b></td>
<td align="center" style="border-left: 1px solid #ddd; padding: 8px;">65.33% ↑</td>
<td align="center" style="padding: 8px;">86.50% ↓</td>
<td align="center" style="padding: 8px;">73.00% ↑</td>
<td align="center" style="padding: 8px;">65.00% ↑</td>
<td align="center" style="border-left: 1px solid #ddd; padding: 8px;">71.32% ↑</td>
<td align="center" style="padding: 8px;">64.86% ↑</td>
<td align="center" style="padding: 8px;">43.75% ↑</td>
<td align="center" style="padding: 8px;">50.00% ↑</td>
</tr>
</tbody>
</table>
How to Get Started
You can load this model using the transformers library:
import torch
from transformers import AutoModelForCausalLM, AutoProcessor
model_id = "zhongyi-zhou/toolgrad-4b"
processor = AutoProcessor.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.bfloat16,
device_map="auto"
)
Citation
If you find this work helpful, please cite our paper:
@misc{zhou2026toolgradefficienttoolusedataset,
title={ToolGrad: Efficient Tool-use Dataset Generation with Textual "Gradients"},
author={Zhongyi Zhou and Kohei Uehara and Haoyu Zhang and Jingtao Zhou and Lin Gu and Ruofei Du and Zheng Xu and Tatsuya Harada},
year={2026},
eprint={2508.04086},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2508.04086},
}