#!/bin/bash
export CUDA_DEVICE_MAX_CONNECTIONS=1
MASTER_ADDR=localhost
MASTER_PORT=6002
NNODES=1
NODE_RANK=0
NPUS_PER_NODE=2
WORLD_SIZE=$(($NPUS_PER_NODE*$NNODES))
CHECKPOINT="your model ckpt path"
TOKENIZER_PATH="your tokenizer path"
TP=1
PP=2
MBS=1
SEQ_LEN=32768
DISTRIBUTED_ARGS="
--nproc_per_node $NPUS_PER_NODE \
--nnodes $NNODES \
--node_rank $NODE_RANK \
--master_addr $MASTER_ADDR \
--master_port $MASTER_PORT
"
torchrun $DISTRIBUTED_ARGS inference.py \
--use-mcore-models \
--tensor-model-parallel-size ${TP} \
--pipeline-model-parallel-size ${PP} \
--num-layers 36 \
--hidden-size 2048 \
--ffn-hidden-size 11008 \
--num-attention-heads 16 \
--group-query-attention \
--num-query-groups 2 \
--tokenizer-type PretrainedFromHF \
--tokenizer-name-or-path ${TOKENIZER_PATH} \
--max-position-embeddings ${SEQ_LEN} \
--seq-length ${SEQ_LEN} \
--make-vocab-size-divisible-by 1 \
--padded-vocab-size 151936 \
--rotary-base 1000000 \
--micro-batch-size ${MBS} \
--swiglu \
--add-qkv-bias \
--disable-bias-linear \
--load ${CHECKPOINT} \
--normalization RMSNorm \
--norm-epsilon 1e-6 \
--position-embedding-type rope \
--hidden-dropout 0 \
--attention-dropout 0 \
--tokenizer-not-use-fast \
--max-new-tokens 256 \
--no-gradient-accumulation-fusion \
--exit-on-missing-checkpoint \
--attention-softmax-in-fp32 \
--seed 42 \
--bf16 \
| tee logs/generate_mcore_qwen25_3b.log