Part 7/8:
On coding benchmarks, M1 exhibits a 65% accuracy rate on Live Code Bench, demonstrating its solid grasp of programming tasks. Notably, in software engineering contexts, M1 excels by correctly repairing bugs in verified environments, achieving a 56% success rate against its peers.
User Access and Deployment Options
For those interested in experimenting with M1, Miniax recommends using VLLM as the backend to optimize memory usage for large expert models. Alternatively, the standard transformers library is also supported to facilitate integration. The model’s flexible licensing allows organizations to deploy it locally, appealing to those with stringent data management protocols.