Model Summary
- Method: WRIT
- Base model:
Qwen/Qwen2.5-14B-Instruct
- Primary use case: research on multi-turn, user-facing, tool-using agents
- Checkpoint format: standard Transformers-compatible safetensors checkpoint
This checkpoint follows the standard Transformers loading interface for Qwen2.5-Instruct models.
Quick Start
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "Henryoung/WRIT-Qwen2.5-14B-Instruct"
tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype="auto",
device_map="auto",
trust_remote_code=True,
)
For tool-use experiments, use the tokenizer chat template included in this repository and the same tool schema format expected by your evaluation environment.
Intended Use
This checkpoint is intended for research on multi-turn tool-use, customer-service agents, and trajectory synthesis methods. It is not intended for deployment without task-specific validation and safety testing.
Limitations
The model may produce incorrect tool calls, incomplete task execution, or unsupported actions outside the target evaluation setting. Users should validate behavior carefully before applying it to any real user-facing workflow.
Citation
@misc{gu2026writwritereadintensivetrajectory,
title={WRIT: Write-Read Intensive Trajectory Synthesis for Multi-Turn User-Facing Agents},
author={Hengrui Gu and Xiaotian Han and Kaixiong Zhou},
year={2026},
eprint={2606.02908},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/2606.02908},
}