Automatic Speech Recognition
Core ML
NeMo
apple-neural-engine
on-device
ios
macos
speech
audio
automatic-speech-translation
canary
fastconformer
kv-cache
fp16
Instructions to use smdesai/canary-1b-v2-coreml with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use smdesai/canary-1b-v2-coreml with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("smdesai/canary-1b-v2-coreml") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
| { | |
| "model": "canary-1b-v2", | |
| "window_samples": 240000, | |
| "precision": "FP16", | |
| "mel_shape": [ | |
| 1, | |
| 128, | |
| 1501 | |
| ], | |
| "enc_states_shape": [ | |
| 1, | |
| 188, | |
| 1024 | |
| ], | |
| "enc_len": 188, | |
| "components": { | |
| "preprocessor": "canary_preprocessor.mlpackage", | |
| "encoder": "canary_encoder.mlpackage" | |
| }, | |
| "optimize": { | |
| "frontend": "preprocessor+encoder (copied from canary_coreml_fp16enc_sliced)", | |
| "decoder": "kv-cache cross+step (copied from canary_coreml_kv)", | |
| "deploy": "compute_units=cpu_and_ne", | |
| "note": "Self-contained KV-cache build: front end (preprocessor + encoder) from canary_coreml_fp16enc_sliced + stateful KV-cache decoder (cross_kv + decoder_kv) from canary_coreml_kv. Run with validate_e2e_kv.py / the Swift KV host." | |
| }, | |
| "decoder_kv": { | |
| "cross_file": "canary_cross_kv.mlpackage", | |
| "step_file": "canary_decoder_kv.mlpackage", | |
| "l_dec": 238, | |
| "t_enc": 188, | |
| "n_layers": 8, | |
| "n_heads": 8, | |
| "head_size": 128, | |
| "max_generation_delta": 50, | |
| "vocab_size": 16384, | |
| "pad": 2, | |
| "eos": 3, | |
| "seed": [ | |
| 16053, | |
| 7, | |
| 4, | |
| 16, | |
| 64, | |
| 64, | |
| 5, | |
| 9, | |
| 11, | |
| 13 | |
| ], | |
| "kv_cache": true, | |
| "neg_inf": -10000.0 | |
| } | |
| } |