fish-speech/train.sh

# export NCCL_P2P_DISABLE=1

# hostfile=""
# deepspeed --hostfile=$hostfile train.py \
#     --deepspeed tools/tts/ds_config.json \
#     --report_to "tensorboard" \
#     --model_name_or_path "fishaudio/speech-lm-300m" \
#     --model_revision "init" \
#     --output_dir "results" \
#     --model_max_length 4096 \
#     --max_steps 500000 \
#     --per_device_train_batch_size 32 \
#     --gradient_accumulation_steps 1 \
#     --save_strategy steps \
#     --save_steps 10000 \
#     --evaluation_strategy steps \
#     --eval_steps 10000 \
#     --learning_rate 1e-3 \
#     --lr_scheduler_type cosine \
#     --adam_beta1 0.9 \
#     --adam_beta2 0.98 \
#     --adam_epsilon 1e-8 \
#     --max_grad_norm 1.0 \
#     --weight_decay 1e-4 \
#     --warmup_steps 10000 \
#     --logging_steps 1 \
#     --gradient_checkpointing True \
#     --remove_unused_columns False \
#     --use_lora False \
#     --bf16 True \
#     --tf32 True

accelerate launch --config_file accelerate-config.yaml train_unconditional.py --config configs/svc.yaml --project test-simple-ne