Instructions to use bezzam/xcodec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bezzam/xcodec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="bezzam/xcodec2")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bezzam/xcodec2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload model
Browse files- config.json +1 -1
config.json
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"resnet_dropout": 0.1,
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"rms_norm_eps": 1e-06,
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"rope_theta": 10000.0,
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"
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"semantic_model_config": {
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"_name_or_path": "facebook/w2v-bert-2.0",
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"activation_dropout": 0.0,
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"resnet_dropout": 0.1,
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"rms_norm_eps": 1e-06,
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"rope_theta": 10000.0,
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"sampling_rate": 16000,
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"semantic_model_config": {
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"_name_or_path": "facebook/w2v-bert-2.0",
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"activation_dropout": 0.0,
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