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---
base_model:
- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
library_name: transformers
license: apache-2.0
---
**Arcee-Maestro-7B-Preview (7B)** is Arcee's first reasoning model trained with reinforment learning. It is based on the Qwen2.5-7B DeepSeek-R1 distillation **DeepSeek-R1-Distill-Qwen-7B** with further GRPO training. Though this is just a preview of our upcoming work, it already shows promising improvements to mathematical and coding abilities across a range of tasks.
### Quantizations
GGUF quants available [here](https://huggingface.co/arcee-ai/Arcee-Maestro-7B-Preview-GGUF)
AWQ quants available [here](https://huggingface.co/arcee-ai/Arcee-Maestro-7B-Preview-AWQ)
### Model Details
- Architecture Base: DeepSeek-R1-Distill-Qwen-7B (Qwen2.5-7B)
- Parameter Count: 7B
- Reinforcement Learning: GRPO with 450,000 **verified** math problems with some coding examples
- License: [Apache-2.0](https://huggingface.co/arcee-ai/Arcee-Maestro-7B-Preview#license)
### Intended Use Cases
- Advanced reasoning
- Mathematics
- Coding
### Evaluations
Arcee Maestro 7B preview shows great gains in mathematics and coding, surpassing O1 preview in many metrics.
### How to use
Below is a sample code snippet using `transformers`:
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
model_name = "arcee-ai/Arcee-Maestro-7B-Preview"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
prompt = "Provide a concise summary of quantum entanglement."
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=150)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```
### Training & Fine-Tuning
- **Initial Training**: Began with DeepSeek-R1-Distill-Qwen-7B
- **GRPO**:
- Trained on 450,000 verified math problems
- Additional bootstrapped coding examples
### Performance
Arcee-Maestro-7B-Preview shows strong performance in mathematics as well as coding, competing against even O1 preview, a model far surprassing its size.
### Limitations
- **Context Length:** 128k Tokens (may vary depending on the final tokenizer settings and system resources).
- **Knowledge Cut-off:** Training data may not reflect the latest events or developments beyond June 2024.
### Ethical Considerations
- **Content Generation Risks:** Like any language model, Arcee-Maestro-7B-Preview can generate potentially harmful or biased content if prompted in certain ways.
### License
**Arcee-Maestro-7B-Preview (7B)** is released under the [Apache-2.0 License](https://www.apache.org/licenses/LICENSE-2.0). You are free to use, modify, and distribute this model in both commercial and non-commercial applications, subject to the terms and conditions of the license.
If you have questions or would like to share your experiences using Arcee-Maestro-7B-Preview (7B), please connect with us on social media. We’re excited to see what you build—and how this model helps you innovate! |