AI가 움직이고 미래가 업데이트됩니다.MiniMax-M3-EAGLE3
**Inferact/MiniMax-M3-EAGLE3** is an EAGLE3 draft model for accelerating inference of MiniMax-M3. It is served end-to-end with **vLLM** and was trained using **TorchSpec** — a torch-native online speculative-decoding training framework that runs FSDP training and vLLM-based target inference concurrently, learning from **MiniMax-M3-regenerated responses and live vLLM-generated hidden states** to match the base model's exact token distribution. The draft is a **1-layer** dense Llama (`LlamaForCausalLMEagle3`, ~3.3 B params) operating on MiniMax-M3's `hidden_size=6144` / `vocab_size=200064`; at serve time it shares the target's embedding and LM head (EAGLE3). See `config.json` for the full architecture. All numbers are measured end-to-end against `MiniMaxAI/MiniMax-M3-MXFP8` served with vLLM at `tensor-parallel-size=4`, `num_speculative_tokens=3`, and `--enforce-eager`. Greedy draft sampling (`topk=1`).
번역 준비 중입니다. 원문을 표시합니다.
**Inferact/MiniMax-M3-EAGLE3** is an EAGLE3 draft model for accelerating inference of MiniMax-M3. It is served end-to-end with **vLLM** and was trained using **TorchSpec** — a torch-native online speculative-decoding training framework that runs FSDP training and vLLM-based target inference concurrently, learning from **MiniMax-M3-regenerated responses and live vLLM-generated hidden states** to match the base model's exact token distribution. The draft is a **1-layer** dense Llama (`LlamaForCausalLMEagle3`, ~3.3 B params) operating on MiniMax-M3's `hidden_size=6144` / `vocab_size=200064`; at serve time it shares the target's embedding and LM head (EAGLE3). See `config.json` for the full architecture. All numbers are measured end-to-end against `MiniMaxAI/MiniMax-M3-MXFP8` served with vLLM at `tensor-parallel-size=4`, `num_speculative_tokens=3`, and `--enforce-eager`. Greedy draft sampling (`topk=1`).