better instruction

z_scripts/e830M_ft.sh

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+#!/bin/bash
+source ~/miniconda3/etc/profile.d/conda.sh
+conda activate voicecraft
+export CUDA_VISIBLE_DEVICES=0,1,2,3
+export WORLD_SIZE=4
+
+dataset=gigaspeech
+mkdir -p ./logs/${dataset}
+
+exp_root="path/to/store/exp_results"
+exp_name=e830M_ft
+dataset_dir="path/to/stored_extracted_codes_and_phonemes/xl" # xs if you only extracted xs in previous step
+encodec_codes_folder_name="encodec_16khz_4codebooks"
+load_model_from="/home/pyp/VoiceCraft/pretrained_models/giga830M.pth"
+
+# export CUDA_LAUNCH_BLOCKING=1 # for debugging
+
+torchrun --nnodes=1 --rdzv-backend=c10d --rdzv-endpoint=localhost:41977 --nproc_per_node=${WORLD_SIZE} \
+../main.py \
+--load_model_from ${load_model_from} \
+--reduced_eog 1 \
+--drop_long 1 \
+--eos 2051 \
+--n_special 4 \
+--pad_x 0 \
+--codebook_weight "[3,1,1,1]" \
+--encodec_sr 50 \
+--num_steps 500000 \
+--lr 0.00001 \
+--warmup_fraction 0.1 \
+--optimizer_name "AdamW" \
+--d_model 2048 \
+--audio_embedding_dim 2048 \
+--nhead 16 \
+--num_decoder_layers 16 \
+--max_num_tokens 20000 \
+--gradient_accumulation_steps 20 \
+--val_max_num_tokens 6000 \
+--num_buckets 6 \
+--audio_max_length 20 \
+--audio_min_length 2 \
+--text_max_length 400 \
+--text_min_length 10 \
+--mask_len_min 1 \
+--mask_len_max 600 \
+--tb_write_every_n_steps 10 \
+--print_every_n_steps 400 \
+--val_every_n_steps 1600 \
+--text_vocab_size 100 \
+--text_pad_token 100 \
+--phn_folder_name "phonemes" \
+--manifest_name "manifest" \
+--encodec_folder_name ${encodec_codes_folder_name} \
+--audio_vocab_size 2048 \
+--empty_token 2048 \
+--eog 2049 \
+--audio_pad_token 2050 \
+--n_codebooks 4 \
+--max_n_spans 3 \
+--shuffle_mask_embedding 0 \
+--mask_sample_dist poisson1 \
+--max_mask_portion 0.9 \
+--min_gap 5 \
+--num_workers 8 \
+--dynamic_batching 1 \
+--dataset $dataset \
+--exp_dir "${exp_root}/${dataset}/${exp_name}" \
+--dataset_dir ${dataset_dir}
+#  >> ./logs/${dataset}/${exp_name}.log 2>&1