Audio-to-Audio
PEFT
Safetensors
Moshi
Turkish
Hindi
speech-to-speech-translation
simultaneous-translation
mimi
lora
tpu
turkish
hindi
Eval Results (legacy)
Instructions to use tiny-aya-translate/tr-hi-s2st-v0.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tiny-aya-translate/tr-hi-s2st-v0.3 with PEFT:
Task type is invalid.
- Moshi
How to use tiny-aya-translate/tr-hi-s2st-v0.3 with Moshi:
# pip install moshi # Run the interactive web server python -m moshi.server --hf-repo "tiny-aya-translate/tr-hi-s2st-v0.3" # Then open https://localhost:8998 in your browser
# pip install moshi import torch from moshi.models import loaders # Load checkpoint info from HuggingFace checkpoint = loaders.CheckpointInfo.from_hf_repo("tiny-aya-translate/tr-hi-s2st-v0.3") # Load the Mimi audio codec mimi = checkpoint.get_mimi(device="cuda") mimi.set_num_codebooks(8) # Encode audio (24kHz, mono) wav = torch.randn(1, 1, 24000 * 10) # [batch, channels, samples] with torch.no_grad(): codes = mimi.encode(wav.cuda()) decoded = mimi.decode(codes) - Notebooks
- Google Colab
- Kaggle
File size: 3,881 Bytes
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"step": 32000,
"config": {
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"data": {
"train_split": "/mnt/data/splits/train.jsonl",
"val_split": "/mnt/data/splits/val.jsonl",
"encoded_dir": "/mnt/data/encoded",
"max_frames": 300,
"bucket_frames": null,
"audio_frame_rate": 12.5,
"num_workers": 32,
"pin_memory": false
},
"train": {
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"batch_size": 8,
"grad_accum": 1,
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"warmup_steps": 1100,
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"depth_chunk_size": 100,
"precision": "bfloat16",
"max_grad_norm": 1.0,
"seed": 42,
"scheduler_total_steps": null,
"per_chip_batch": 2,
"schedule": "wsd",
"wsd_anneal_steps": 11000,
"wsd_anneal_frac": 0.1,
"weight_decay": 0.01,
"adam_beta1": 0.9,
"adam_beta2": 0.999,
"adam_eps": 1e-08,
"allow_fresh_optimizer": false,
"use_scan_layers": true,
"xla_grad_checkpoint": true,
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"debug_input_sharding": false,
"early_stop_patience": 10,
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"clip_grad_norm": 1.0,
"log_grad_norm": true,
"fsdp_barrier_hook": false,
"micro_mark_step": true,
"final_canonical_save": true
},
"loss": {
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"audio_weight": 1.0,
"text_weight_curriculum_frac": 0.0,
"composite_text_w": 0.4,
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1.0,
1.5,
1.5,
2.0,
2.0,
2.0,
2.0
],
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"unmask_k0": 1
},
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"lr_full_ft": 5e-05,
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"lr_depth": 0.0001,
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"lr_text_embed": 0.0005,
"lr_depth_blocks": 1e-05
},
"logging": {
"log_every": 25,
"save_every": 1000,
"audio_every": 5000,
"audio_ar_frames": 50,
"val_every": 250,
"val_max_batches": 25,
"val_on_tpu": true,
"val_per_chip_batch": 8,
"tpu_telemetry_every": 250,
"save_dir": "gs://tinyaya-stage2-eu/checkpoints/stage2-v6e16-mh-v03-r2",
"log_spaced_saves": true,
"save_at_steps": null,
"async_checkpoint_upload": true,
"wandb_project": "tinyaya-stage2-tpu",
"wandb_run_name": "v0.3-long-horizon-mh-r2",
"use_wandb": true,
"wandb_tags": [
"v0.3",
"multi-host",
"wsd"
],
"push_to_hub": true,
"hub_repo_id": "tiny-aya-translate/tr-hi-s2st-v0.3",
"hub_private": true,
"diag_metrics": true,
"keep_last_n": 0,
"keep_local_checkpoints": false
},
"perf": {
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"warmup_skip_steps": 25,
"xprof_trace_labels": false
},
"lora": {
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"alpha": 64,
"dropout": 0.05,
"use_rslora": true,
"target_modules": [
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"k_proj",
"v_proj",
"o_proj",
"gate_proj",
"up_proj",
"down_proj",
"embed_tokens"
],
"lora_exclude_top": 0,
"num_full_ft_layers": 0,
"depth_unfreeze_blocks": 0
}
},
"wandb_run_id": "xzcb60bl",
"best_val": 3.0128649473190308,
"patience_left": 8,
"resumes": 0,
"files": {
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"model_audio_embed.pt": 8394415,
"audio_heads.pt": 8390277,
"peft_adapter/adapter_config.json": 1122,
"peft_adapter/README.md": 5202,
"peft_adapter/adapter_model.safetensors": 1220179520
}
} |