Instructions to use bezzam/Qwen3-ForcedAligner-0.6B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bezzam/Qwen3-ForcedAligner-0.6B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="bezzam/Qwen3-ForcedAligner-0.6B")# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("bezzam/Qwen3-ForcedAligner-0.6B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 464 Bytes
e9042e8 40b9d41 e9042e8 b1af456 e9042e8 254253d e9042e8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | {
"feature_extractor": {
"chunk_length": 30,
"dither": 0.0,
"feature_extractor_type": "Qwen3ASRFeatureExtractor",
"feature_size": 128,
"hop_length": 160,
"n_fft": 400,
"n_samples": 480000,
"n_window": 50,
"nb_max_frames": 3000,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": false,
"sampling_rate": 16000
},
"processor_class": "Qwen3ASRProcessor",
"timestamp_segment_time": 80
}
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