sample_rate: 24_000 audio_backend: "vocos" models: - name: "ar+nar" size: "full" resp_levels: 8 prom_levels: 8 tasks: 8 langs: 2 tones: 1 arch_type: llama training: False version: 5 attention: auto dropout: 0.1 loss_factors: text: 0.01 prom: 0.5 resp: 1.0 capabilities: ["ar", "nar"] experimental: audio_embedding_sums: False unified_position_ids: False split_classifiers: True hyperparameters: autotune: False autotune_params: start_profile_step: 1 end_profile_step: 50 num_tuning_micro_batch_sizes: 8 batch_size: 16 gradient_accumulation_steps: 8 gradient_clipping: 1.0 warmup_steps: 250 optimizer: Prodigy learning_rate: 1.0 torch_optimizer: True scheduler: "" # ScheduleFree torch_scheduler: True evaluation: batch_size: 16 frequency: 1000 size: 16 steps: 500 ar_temperature: 0.95 nar_temperature: 0.25 load_disabled_engines: True trainer: #no_logger: True ddp: False check_for_oom: False iterations: 1_000_000 save_tag: step save_on_oom: True save_on_quit: True save_frequency: 500 export_on_save: True keep_last_checkpoints: 8 aggressive_optimizations: False load_disabled_engines: False gradient_checkpointing: True #load_state_dict: True strict_loading: False #load_tag: "9500" #load_states: False #restart_step_count: True gc_mode: None # "global_step" weight_dtype: bfloat16 amp: True backend: deepspeed deepspeed: inferencing: True zero_optimization_level: 0 use_compression_training: False amp: False load_webui: False inference: backend: deepspeed audio_backend: "vocos" normalize: False weight_dtype: bfloat16 amp: True optimizations: injects: False replace: True linear: False embedding: False optimizers: True bitsandbytes: False dadaptation: False bitnet: False fp8: False dataset: speaker_name_getter: "lambda p: f'{p.parts[-3]}_{p.parts[-2]}'" speaker_group_getter: "lambda p: f'{p.parts[-3]}'" speaker_languages: ja: [] use_hdf5: True use_metadata: True hdf5_flag: r validate: True workers: 6 cache: True duration_range: [24.0, 32.0] random_utterance: 1.0 max_prompts: 1 prompt_duration_range: [3.0, 9.0] max_resps: 1 p_resp_append: 0.25 sample_type: path # path # speaker tasks_list: [ "tts" ] # , [ "tts", "tts-c", "ns", "sr", "tse", "cse", "nse", "tts"] training: [] validation: [] noise: []