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arcee-ai/Arcee-Maestro-7B-Preview

sourceHugging Faceapache-2.0updated 2y agoView on Hugging Face
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Model Card

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

AWQ quants available here

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

Intended Use Cases

  • —Advanced reasoning
  • —Mathematics
  • —Coding

Evaluations

image/png

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. 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!