MiniMaxAI

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MiniMax-M2.1

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When I`m running MiniMax-2.1 on H200 with sglang command:
python3 -m sglang.launch_server --model /volume/models/MiniMaxAI/MiniMax-M2.1/snapshots/17f852dfda7d63c61b1107d47552bb30488ffbee --trust-remote-code --tp-size 2 --pp-size 2 --mem-fraction-static 0.85 --chunked-prefill-size 20480 --page-size 64 --cuda-graph-max-bs 64 --enable-metrics

the error occurs:

[2026-01-12 02:39:23 PP3 TP1] Scheduler hit an exception: Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/sglang/srt/managers/scheduler.py", line 2653, in run_scheduler_process
    scheduler = Scheduler(
  File "/usr/local/lib/python3.10/dist-packages/sglang/srt/managers/scheduler.py", line 316, in __init__
    self.tp_worker = TpModelWorker(
  File "/usr/local/lib/python3.10/dist-packages/sglang/srt/managers/tp_worker.py", line 245, in __init__
    self._model_runner = ModelRunner(
  File "/usr/local/lib/python3.10/dist-packages/sglang/srt/model_executor/model_runner.py", line 361, in __init__
    self.initialize(min_per_gpu_memory)
  File "/usr/local/lib/python3.10/dist-packages/sglang/srt/model_executor/model_runner.py", line 436, in initialize
    self.load_model()
  File "/usr/local/lib/python3.10/dist-packages/sglang/srt/model_executor/model_runner.py", line 804, in load_model
    self.model = get_model(
  File "/usr/local/lib/python3.10/dist-packages/sglang/srt/model_loader/__init__.py", line 28, in get_model
    return loader.load_model(
  File "/usr/local/lib/python3.10/dist-packages/sglang/srt/model_loader/loader.py", line 600, in load_model
    self.load_weights_and_postprocess(
  File "/usr/local/lib/python3.10/dist-packages/sglang/srt/model_loader/loader.py", line 608, in load_weights_and_postprocess
    model.load_weights(weights)
  File "/usr/local/lib/python3.10/dist-packages/sglang/srt/models/minimax_m2.py", line 882, in load_weights
    param = params_dict[name]
KeyError: 'model.layers.37.block_sparse_moe.e_score_correction_bias'

[2026-01-12 02:39:23] Received sigquit from a child process. It usually means the child failed.