Instructions to use SHENMU007/neunit-ks with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SHENMU007/neunit-ks with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="SHENMU007/neunit-ks")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("SHENMU007/neunit-ks") model = AutoModelForAudioClassification.from_pretrained("SHENMU007/neunit-ks", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 0
Browse files- config.json +4 -6
- pytorch_model.bin +2 -2
- training_args.bin +1 -1
config.json
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"hidden_dropout": 0.1,
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"hidden_size": 768,
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"id2label": {
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"0": "
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"stop": "2"
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"layer_norm_eps": 1e-05,
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"layerdrop": 0.0,
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"hidden_dropout": 0.1,
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"hidden_size": 768,
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"id2label": {
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"label2id": {
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"down": "0",
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"stop": "1"
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"layer_norm_eps": 1e-05,
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"layerdrop": 0.0,
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pytorch_model.bin
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training_args.bin
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