--- base_model: - MiniMaxAI/MiniMax-M2.7 language: - en library_name: transformers license: other license_name: modified-mit license_link: https://huggingface.co/MiniMaxAI/MiniMax-M2.7/blob/main/LICENSE --- # Model Overview - **Model Architecture:** MiniMaxM2ForCausalLM - **Input:** Text - **Output:** Text - **Supported Hardware Microarchitecture:** AMD MI300 MI350/MI355 - **ROCm**: --- - **PyTorch**: --- - **Transformers**: --- - **Operating System(s):** Linux - **Inference Engine:** [SGLang](https://docs.sglang.ai/)/[vLLM](https://docs.vllm.ai/en/latest/) - **Model Optimizer:** [AMD-Quark](https://quark.docs.amd.com/latest/index.html) - **Weight quantization:** OCP MXFP4, Static - **Activation quantization:** OCP MXFP4, Dynamic # Model Quantization The model was quantized from [MiniMaxAI/MiniMax-M2.7](https://huggingface.co/MiniMaxAI/MiniMax-M2.7) using [AMD-Quark](https://quark.docs.amd.com/latest/index.html). The weights are quantized to MXFP4 and activations are quantized to MXFP4. **Quantization scripts:** TBD For further details or issues, please refer to the AMD-Quark documentation or contact the respective developers. # Evaluation TBD ### Accuracy
| Benchmark | MiniMaxAI/MiniMax-M2.7 | amd/MiniMax-M2.7-MXFP4(this model) | Recovery |
| gsm8k (flexible-extract) | TBD | TBD | TBD |