Arcee Maestro 7B preview shows great gains in mathematics and coding, surpassing O1 preview in many metrics.
1from transformers import AutoTokenizer, AutoModelForCausalLM
2
3model_name = "arcee-ai/Arcee-Maestro-7B-Preview"
4tokenizer = AutoTokenizer.from_pretrained(model_name)
5model = AutoModelForCausalLM.from_pretrained(model_name)
6
7prompt = "Provide a concise summary of quantum entanglement."
8inputs = tokenizer(prompt, return_tensors="pt")
9outputs = model.generate(**inputs, max_new_tokens=150)
10print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Arcee-Maestro-7B-Preview shows strong performance in mathematics as well as coding, competing against even O1 preview, a model far surprassing its size.
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!