Instructions to use TechHara/timestamps-asr-canary-ctc-mlx-q8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use TechHara/timestamps-asr-canary-ctc-mlx-q8 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir timestamps-asr-canary-ctc-mlx-q8 TechHara/timestamps-asr-canary-ctc-mlx-q8
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
canary-1b-v2 β timestamps_asr_model β MLX q8
Quantized MLX port of the timestamps_asr_model bundled inside
nvidia/canary-1b-v2. It is
the dedicated CTC forced-alignment head paired with canary; vocabulary is
byte-identical to canary's sentencepiece (16 384 pieces).
| Architecture | 24-layer Conformer encoder + 1Γ1 CTC head |
| Params | 626 M |
| Mel features | 128 |
| d_model | 1024 |
| CTC vocab | 16 384 + blank |
| Subsampling | 8Γ (dw_striding) |
| Self-attention | full rel-pos |
| Quantization | bits=8, group_size=64 (MLX default) |
| Source | extracted from canary-1b-v2.nemo |
Files
| File | Size |
|---|---|
config.json |
preprocessor + encoder + CTC config (with inline vocab) |
model.safetensors |
q8 weights + bf16 scales/biases |
tokenizer.model |
canary's sentencepiece (1:1 copy) |
License
CC-BY-4.0 β inherited from nvidia/canary-1b-v2.
- Downloads last month
- 14
Model size
0.2B params
Tensor type
BF16
Β·
U32 Β·
Hardware compatibility
Log In to add your hardware
Quantized
Inference Providers NEW
This model isn't deployed by any Inference Provider. π Ask for provider support
Model tree for TechHara/timestamps-asr-canary-ctc-mlx-q8
Base model
nvidia/canary-1b-v2