74 lines
3.1 KiB
Markdown
74 lines
3.1 KiB
Markdown
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---
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base_model:
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- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
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library_name: transformers
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license: apache-2.0
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---
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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 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.
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### Quantizations
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GGUF quants available [here](https://huggingface.co/arcee-ai/Arcee-Maestro-7B-Preview-GGUF)
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AWQ quants available [here](https://huggingface.co/arcee-ai/Arcee-Maestro-7B-Preview-AWQ)
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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!
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