Feature Extraction
Transformers
Safetensors
meralion_bestrq
speech
best-rq
meralion
meralion-2
custom_code
Instructions to use MERaLiON/MERaLiON-SpeechEncoder-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MERaLiON/MERaLiON-SpeechEncoder-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="MERaLiON/MERaLiON-SpeechEncoder-2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MERaLiON/MERaLiON-SpeechEncoder-2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 503 Bytes
f9f057c c2c8318 f9f057c c2c8318 f9f057c c2c8318 f9f057c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"auto_map": {
"AutoFeatureExtractor": "processing_bestrq_conformer.ModifiedWhisperFeatureExtractor",
"AutoProcessor": "processing_bestrq_conformer.ModifiedWhisperFeatureExtractor"
},
"chunk_length": 120,
"feature_extractor_type": "ModifiedWhisperFeatureExtractor",
"feature_size": 80,
"hop_length": 160,
"n_fft": 400,
"n_samples": 1920000,
"nb_max_frames": 12000,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 16000
}
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