Instructions to use bezzam/xcodec2-processor-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bezzam/xcodec2-processor-test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bezzam/xcodec2-processor-test")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("bezzam/xcodec2-processor-test") model = AutoModelForMultimodalLM.from_pretrained("bezzam/xcodec2-processor-test") - Notebooks
- Google Colab
- Kaggle
File size: 270 Bytes
35c55ab | 1 2 3 4 5 6 7 8 9 10 11 12 | {
"feature_extractor_type": "SeamlessM4TFeatureExtractor",
"feature_size": 80,
"num_mel_bins": 80,
"padding_side": "right",
"padding_value": 1,
"processor_class": "Xcodec2Processor",
"return_attention_mask": true,
"sampling_rate": 16000,
"stride": 2
}
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