Instructions to use yapwithai/kyutai-stt-1b-en_fr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Moshi
How to use yapwithai/kyutai-stt-1b-en_fr with Moshi:
# pip install moshi # Run the interactive web server python -m moshi.server --hf-repo "yapwithai/kyutai-stt-1b-en_fr" # 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("yapwithai/kyutai-stt-1b-en_fr") # 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
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| "card": 2048, | |
| "n_q": 32, | |
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| "dim": 2048, | |
| "text_card": 8000, | |
| "existing_text_padding_id": 3, | |
| "num_heads": 16, | |
| "num_layers": 16, | |
| "hidden_scale": 4.125, | |
| "causal": true, | |
| "layer_scale": null, | |
| "context": 750, | |
| "max_period": 100000.0, | |
| "gating": "silu", | |
| "norm": "rms_norm_f32", | |
| "positional_embedding": "rope", | |
| "depformer_dim": 1024, | |
| "depformer_num_heads": 16, | |
| "depformer_num_layers": 6, | |
| "depformer_dim_feedforward": null, | |
| "depformer_multi_linear": true, | |
| "depformer_pos_emb": "none", | |
| "depformer_weights_per_step": true, | |
| "conditioners": {}, | |
| "cross_attention": false, | |
| "model_id": { | |
| "sig": "70f8f0ea", | |
| "epoch": 500 | |
| }, | |
| "lm_gen_config": { | |
| "temp": 0.0, | |
| "temp_text": 0.0, | |
| "top_k": 250, | |
| "top_k_text": 50 | |
| }, | |
| "stt_config": { | |
| "audio_delay_seconds": 0.5, | |
| "audio_silence_prefix_seconds": 0.0 | |
| }, | |
| "model_type": "stt", | |
| "mimi_name": "mimi-pytorch-e351c8d8@125.safetensors", | |
| "tokenizer_name": "tokenizer_en_fr_audio_8000.model" | |
| } | |