Instructions to use BeatThis/BeatThisModels with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use BeatThis/BeatThisModels with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://BeatThis/BeatThisModels") - Notebooks
- Google Colab
- Kaggle
Upload folder using huggingface_hub
Browse files- cnn_data/bell_ride_model.pkl +3 -0
- cnn_data/cymbals_model.pkl +3 -0
- cnn_data/hh_model.pkl +3 -0
- cnn_data/toms_model.pkl +3 -0
cnn_data/bell_ride_model.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:5db5a5a9702ffec52e0f093886a34ca6f30ebbae1acb14dd785feb5a3738dae7
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size 282
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cnn_data/cymbals_model.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:acdc7457ad9ab34bde59141bc34ccbcfd079a3e9610c46b6298656bbdbd2a413
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size 282
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cnn_data/hh_model.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:f95c4d29b8926aaaa62f873a716af8e8ff87b921d7aae95bc46bf3bb16cc8b72
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size 282
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cnn_data/toms_model.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:8ed16d31705bf039906e45cb07ce8de121756ec3dc92caa7a90b805a15715246
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size 282
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