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library_name: transformers
datasets:
- openGPT-X/gsm8kx
language:
- zho
- eng
- fra
- spa
- por
- deu
- ita
- rus
- jpn
- kor
- vie
- tha
- ara
base_model:
- Qwen/Qwen2.5-3B-Instruct
pipeline_tag: text-generation
---
# German R1
**Introducing German-R1. We are so back!!11**
- 🇩🇪 German R1 is a reasoning model almost equivalent to OpenAI‘s o3 or DeepSeek‘s R1 - but it thinks in German!
- 🇩🇪 German R1 is so efficient that is was build without any government funding.
- 🇩🇪 German R1 was only trained with legally imported H100s in less than five minutes.
- Please do NOT take this too serious.
## Context
See Linkedin: https://www.linkedin.com/posts/activity-7294337496023269376-ZBkI
## Usage
You can run the model as follows:
```python
from transformers import pipeline, set_seed
import json
set_seed(42)
pipe = pipeline("text-generation", "malteos/german-r1")
# from gsm8k test set
question = "James beschließt, 3-mal pro Woche 3 Sprints zu laufen. Er läuft 60 Meter pro Sprint. Wie viele Meter läuft er insgesamt pro Woche?"
expected_answer = "540"
# xml reasoning and answer format
system_prompt = """
Antworte auf deutsch und in diesem Format:
<reasoning>
...
</reasoning>
<answer>
...
</answer>
"""
messages = [
{
"role": "system",
"content": system_prompt,
},
{"role": "user", "content": dataset["question"][3]},
]
response = pipe(messages, max_new_tokens=256)
print(json.dumps(response, indent=4, ensure_ascii=False))
```
The output should look like this (correct answer: 540)
```json
[
{
"generated_text": [
{
"role": "system",
"content": "\nAntworte auf deutsch und in diesem Format:\n<reasoning>\n...\n</reasoning>\n<answer>\n...\n</answer>\n"
},
{
"role": "user",
"content": "James beschließt, 3-mal pro Woche 3 Sprints zu laufen. Er läuft 60 Meter pro Sprint. Wie viele Meter läuft er insgesamt pro Woche?"
},
{
"role": "assistant",
"content": "<reasoning>\nJames läuft 3 Sprints pro Tag, wobei jeder Sprint 60 Meter beträgt. Deshalb läuft er pro Tag 3 Sprints * 60 Meter/Sprint = 180 Meter. James läuft 3 Mal pro Woche, also läuft er insgesamt 180 Meter * 3 = 540 Meter pro Woche.\n</reasoning>\n<answer>\n540\n</answer>\n"
}
]
}
]
```
## Training details
- Base model: Qwen2.5-3B-Instruct
- Implementation: based on [GRPO demo](https://gist.github.com/willccbb/4676755236bb08cab5f4e54a0475d6fb) by [will brown](https://x.com/willccbb) + language identification reward
- Training data: German subset of [openGPT-X/gsm8kx](https://huggingface.co/datasets/openGPT-X/gsm8kx/) (machine translated from the English gsm8k)
## License
[Qwen research](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct/blob/main/LICENSE) |