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--- |
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base_model: |
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- arcee-ai/Arcee-Maestro-7B-Preview |
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library_name: transformers |
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license: apache-2.0 |
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--- |
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# GGUF Quantization of Arcee-Maestro-7B-Preview |
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**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 GPRO 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. |
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### Model Details |
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- Architecture Base: DeepSeek-R1-Distill-Qwen-7B (Qwen2.5-7B) |
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- Parameter Count: 7B |
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- Reinforcement Learning: GRPO with 450,000 **verified** math problems with some coding examples |
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- License: [Apache-2.0](https://huggingface.co/arcee-ai/Arcee-Maestro-7B-Preview#license) |
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### Intended Use Cases |
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- Advanced reasoning |
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- Mathematics |
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- Coding |
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### Evaluations |
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Arcee Maestro 7B preview shows great gains in mathematics and coding, surpassing O1 preview in many metrics. |
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### How to use |
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Below is a sample code snippet using `transformers`: |
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```python |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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model_name = "arcee-ai/Arcee-Maestro-7B-Preview" |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained(model_name) |
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prompt = "Provide a concise summary of quantum entanglement." |
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inputs = tokenizer(prompt, return_tensors="pt") |
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outputs = model.generate(**inputs, max_new_tokens=150) |
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print(tokenizer.decode(outputs[0], skip_special_tokens=True)) |
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``` |
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### Training & Fine-Tuning |
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- **Initial Training**: Began with DeepSeek-R1-Distill-Qwen-7B |
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- **GRPO**: |
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- Trained on 450,000 verified math problems |
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- Additional bootstrapped coding examples |
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### Performance |
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Arcee-Maestro-7B-Preview shows strong performance in mathematics as well as coding, competing against even O1 preview, a model far surprassing its size. |
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### Limitations |
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- **Context Length:** 128k Tokens (may vary depending on the final tokenizer settings and system resources). |
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- **Knowledge Cut-off:** Training data may not reflect the latest events or developments beyond June 2024. |
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### Ethical Considerations |
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- **Content Generation Risks:** Like any language model, Arcee-Maestro-7B-Preview can generate potentially harmful or biased content if prompted in certain ways. |
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### License |
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**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. |
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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! |
