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michalsr
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Model Details
Model Provider
michalsr
Model Tree
Qwen/Qwen3-VL-8B-Instruct
Input Modalities
Output Modalities
Supported Functionality
python
from transformers import AutoProcessor, AutoModelForCausalLMprocessor = AutoProcessor.from_pretrained("michalsr/toolmerge-planner-grpo")model = AutoModelForCausalLM.from_pretrained("michalsr/toolmerge-planner-grpo",torch_dtype="bfloat16",)
To use inside ToolMerge, override the planner checkpoint at the CLI:
bash
toolmerge config=configs/m2m/qwen3_8.yaml \model.base=michalsr/toolmerge-planner-grpo
| Setting | Value |
|---|---|
| Base model | Qwen/Qwen3-VL-8B-Instruct |
| Reward | frames_in_gt=1.0, consistency=1.0 |
| Training data | train_correct_uniform_8f_clip_max1.json (filtered M2M train split, ~1500 items) |
| Optimizer | paged_adamw_8bit, lr=1e-6, bf16 |
| Compute | 2 nodes × 4 GPUs |
| Step | global_step=50 |
| Framework | TRL 0.27.2, transformers 4.57.6, PyTorch 2.10.0 |
Full training config: training/configs/m2m_grpo.yaml
in the ToolMerge repo.
bibtex
@misc{shlapentokhrothman2026decomposingqueriestoolcalls,title = {Decomposing Queries into Tool Calls for Long-Video Keyframe Retrieval},author = {Michal Shlapentokh-Rothman and Prachi Garg and Yu-Xiong Wang and Derek Hoiem},year = {2026},eprint = {2605.23826},archivePrefix = {arXiv},primaryClass = {cs.CV},url = {https://arxiv.org/abs/2605.23826},}
Cite the GRPO method:
bibtex
@article{shao2024deepseekmath,title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}},author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo},year = 2024,eprint = {arXiv:2402.03300},}
Code repo: https://github.com/michalsr/ToolMerge.