---
library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
base_model: Qwen/Qwen2.5-Coder-14B-Instruct
datasets:
  - May2222/P-Bench
language:
  - en
tags:
  - statistics
  - hypothesis-testing
  - tool-use
---

# Fisher-R1-14B

Fisher-R1-14B is an open-weight LLM agent for reliable hypothesis testing. It is post-trained from Qwen2.5-Coder-14B-Instruct on synthetic executable statistical tasks, using supervised fine-tuning followed by reinforcement learning with verified statistical rewards.

The model is designed to inspect data, select and execute an appropriate statistical test, report a p-value, and draw a conclusion. It is evaluated on [P-Bench](https://huggingface.co/datasets/May2222/P-Bench).

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "May2222/Fisher-R1-14B"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id,
    torch_dtype="auto",
    device_map="auto",
)
```

For the training setup, evaluation protocol, and results, see [Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing](https://arxiv.org/abs/2608.07437).

## Citation

```bibtex
@article{miao2026fisherr1,
  title   = {Fisher-R1: Training LLM Agents for Reliable Hypothesis Testing},
  author  = {Miao, Jiacheng and Mu, Jin and Chen, Guanhua and Zou, James},
  journal = {arXiv preprint arXiv:2608.07437},
  year    = {2026},
  url     = {https://arxiv.org/abs/2608.07437}
}
```